Computer and new operations regarding technology development

ABSTRACT

A computer includes a computing entity (CE) processing core section, a technology level (TL) co-processor section, a system database section, and a memory section. The database section stores TL data operands regarding quantified technologies and the memory section stores a CE operating system, a TL operating system, TL system applications, and TL user applications. The CE processing core section executes the TL operating system and the CE operating system. The TL co-processor section executes one or more TL system applications, in accordance with control of the TL operating system and the CE operating system, to produce TL data operands regarding technical challenges, level of innovation, and ideal protection of a quantified technology from a large number of MSBTP documents.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present U.S. Utility Patent application claims priority pursuant to35 U.S.C. § 119(e) to U.S. Provisional Application No. 63/317,380,entitled “PATENT DATA AND ANALYTICS COMPUTING SYSTEM”, filed Mar. 7,2022; all of which is hereby incorporated herein by reference in itsentirety and made part of the present U.S. Utility Patent Applicationfor all purposes.

The present U.S. Utility Patent Application also claims prioritypursuant to 35 U.S.C. § 119(e) to U.S. Provisional Application No.63/488,227, entitled “IMPROVED COMPUTER FOR ENHANCING AND/OR EVOLVINGTECHNOLOGY”, filed Mar. 3, 2023; all of which is hereby incorporatedherein by reference in its entirety and made part of the present U.S.Utility Patent Application for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not Applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

The disclosed subject matter relates to a variety of technologies andmore particularly to an improved computer for technology.

DESCRIPTION OF RELATED ART

Technology is defined as the application of scientific knowledge forpractical purposes. The scientific knowledge often applied are physicalsciences and/or life sciences but may further include social sciencesand/or political sciences. Physical sciences involve the study of thephysical world and/or the universe. Life sciences involve the study ofliving things, human and non-human.

The physical sciences are divided and sub-divided into a plurality ofphysical science fields (e.g., electrical engineering, computer science,data science, physics, etc.). Similarly, the life sciences are dividedand sub-divided into a plurality of life science fields (e.g., biology,human anatomy, physiology, botany, etc.). The advancement of most, ifnot all, of the scientific fields rely on data analytics provided bycomputers.

Many advancements in the various scientific fields are innovative andwarrant protection. There is a variety of protection mechanisms toprotect such innovations; which include legal protection, physicalprotection, and virtual protection. Creating, identifying, managing,tracking, protecting, utilizing, organizing, and/or evolving innovationswithin a scientific field is often an overwhelming task and, as such, isoften not done or is done ineffectively and/or inefficiently. When thetask is over multiple scientific fields, it is even more daunting.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1A is a schematic block diagram of an example of a conventionalpatent process;

FIG. 1B is a schematic block diagram of an example of an annual budgetfor a conventional patent process;

FIG. 1C is a schematic block diagram of an example of a conventionalpatent process with accompanying components of an annual budget;

FIG. 1D is a schematic block diagram of an example of invention types ofa conventional patent process;

FIG. 1E is a schematic block diagram of an example of a conventionalpatent process with accompanying elements of the process;

FIG. 1F is a schematic block diagram of an example of a conventionalpatent process with accompanying support services for the process;

FIG. 1G is a schematic block diagram of another example of aconventional patent process with accompanying support services for theprocess;

FIG. 1H is a schematic block diagram of another example of aconventional patent process with accompanying support services for theprocess;

FIG. 11 is a schematic block diagram of an example of identifying anddisclosing inventions of a conventional patent process;

FIG. 1J is a schematic block diagram of an example of a timeline of aconventional patent process;

FIG. 1K is a schematic block diagram of an example of limitations of aconventional patent process;

FIG. 1L is a schematic block diagram of another example of limitationsof a conventional patent process;

FIG. 2 is a schematic block diagram of an example a company's valueproposition;

FIGS. 3A through 3C are a logic diagram of a method for execution by animproved computer for technology;

FIG. 4A is a schematic block diagram of an embodiment of an improvedcomputer for technology;

FIG. 4B is a schematic block diagram of another embodiment of animproved computer for technology;

FIG. 4C is a diagram of an embodiment of operating system functions ofan improved computer for technology;

FIGS. 5A through 5E are schematic block diagram of embodiments ofcomputing entities that are part of an improved computer for technology;

FIGS. 6A through 6G are schematic block diagram of embodiments ofcomputing devices that form at least a portion of a computing entity;

FIG. 7 is a schematic block diagram of an embodiment of a database;

FIG. 8A is a diagram of an example of physical science technicalcategories;

FIG. 8B is a diagram of an example of life science technical categories;

FIG. 9A is a diagram of an example of electrical technology itemcategories;

FIG. 9B is a diagram of an example of communication technology itemcategories;

FIG. 9C is a diagram of an example of information technology itemcategories;

FIG. 9D is a diagram of an example of energy & power technology itemcategories;

FIG. 10A is a Venn diagram of communication technology, informationtechnology, and electrical technology;

FIG. 10B is a Venn diagram of communication technology, informationtechnology, and electrical technology with energy & power technology;

FIG. 10C is a Venn diagram of communication technology, informationtechnology, and electrical technology with chemical technology;

FIG. 10D is a Venn diagram of communication technology, informationtechnology, and electrical technology with mechanical & industrialtechnology;

FIG. 10E is a Venn diagram of communication technology, informationtechnology, and electrical technology with medical technology;

FIG. 10F is a Venn diagram of communication technology, informationtechnology, and electrical technology with agriculture technology;

FIG. 10G is a Venn diagram of communication technology, informationtechnology, and electrical technology with biological technology;

FIG. 10H is a Venn diagram of communication technology, informationtechnology, and electrical technology with biochemical technology;

FIG. 101 is a Venn diagram of communication technology, informationtechnology, and electrical technology with genetics technology;

FIG. 10J is a Venn diagram of communication technology, informationtechnology, and electrical technology with ecological technology;

FIG. 11A is a schematic block diagram of an example of a service supplychain;

FIG. 11B is a schematic block diagram of an example of a product supplychain;

FIG. 12A is a schematic block diagram of an example of a high-leveltechnology relational map;

FIG. 12B is a schematic block diagram of an example of a technologyrelational map;

FIGS. 13A through 13E are schematic block diagram of embodiments ofitems that include one or more market-tech units (MTUs);

FIG. 14A is a schematic block diagram of an example of a market-techunit (MTU) relationship map;

FIG. 14B is a schematic block diagram of another example of amarket-tech unit (MTU) relationship map;

FIG. 15A is a schematic block diagram of an example of a market-techunit (MTU) relationships;

FIG. 15B is a schematic block diagram of another example of amarket-tech unit (MTU) relationships;

FIG. 15C is a schematic block diagram of another example of amarket-tech unit (MTU) relationships;

FIG. 16A is a schematic block diagram of an example of a softwaremarket-tech unit (MTU) relationships;

FIG. 16B is a schematic block diagram of another example of a softwaremarket-tech unit (MTU) relationships;

FIG. 17 is a flow diagram of an example of a technology development (oneor more market-tech units [MTUs]), business development, patentprotection of the technology, and business success;

FIG. 18 is a logic diagram of an example of value of patent protectedtechnology (one or more market-tech units [MTUs]);

FIG. 19 is a diagram of an example of a full spectrum of invention typesfor patenting to patent protect a technology (one or more market-techunits[MTUs]);

FIG. 20 is a schematic block diagram of an embodiment of a re-engineeredpatent process for effective and efficient patent protection, use,and/or value of a technology (one or more market-tech units [MTUs]);

FIG. 21A is a schematic block diagram of another embodiment of are-engineered patent process for effective and efficient patentprotection, use, and/or value of a technology (one or more market-techunits [MTUs]);

FIG. 21B is a schematic block diagram of an example of data for are-engineered patent process for effective and efficient patentprotection, use, and/or value of a technology (one or more market-techunits [MTUs]);

FIG. 22 is a flow diagram of an example of a generating a patentprotection plan for a technology (one or more market-tech units [MTUs)];

FIG. 23 is a flow diagram of another example of a generating a patentprotection plan for a technology (one or more market-tech units [MTUs)];

FIG. 24 is a schematic block diagram of a further embodiment of animproved computer for technology;

FIG. 25 is a schematic block diagram of a further embodiment of animproved computer for technology;

FIG. 26 is a schematic block diagram of a further embodiment of animproved computer for technology;

FIG. 27 is a schematic block diagram of a further embodiment of animproved computer for technology;

FIG. 28 is a schematic block diagram of a further embodiment of animproved computer for technology;

FIG. 29 is a flow diagram of another example of a generating a patentprotection plan for a technology (one or more market-tech units [MTUs)];

FIG. 30 is a schematic block diagram of a further embodiment of animproved computer for technology;

FIG. 31 is a diagram of an example of a relative number of inventionsbeing created over the life of a technology (one or more market-techunits [MTUs)];

FIG. 32 is a diagram of an example of a relative invention breadth ofinventions being created over the life of a technology (one or moremarket-tech units [MTUs)];

FIG. 33 is a diagram of an example of a relative total number ofinventions, a relative ideal number of inventions over the life of atechnology (one or more market-tech units [MTUs)], and existinginventions protected to date;

FIG. 34 is a flow diagram of another example of a generating a patentprotection plan for multiple market-tech units [MTUs];

FIG. 35 is a logic diagram of an example of a method for generating apatent protection plan regarding a technology (one or more market-techunits [MTUs)];

FIG. 36 is a diagram of an example of implementing a method forgenerating a patent protection plan regarding a technology (one or moremarket-tech units [MTUs)];

FIG. 37 is a schematic block diagram of an example of a graphical userinterface (GUI) of an improved computer for technology;

FIG. 38A is a schematic block diagram of an example of auser-interactive graphical representation of a market-tech unit (MTU)data record of an MTU database;

FIG. 38B is a schematic block diagram of an example of auser-interactive graphical representation of an MTU naming and catalogsection of a market-tech unit (MTU) data record of an MTU database;

FIG. 39 is a schematic block diagram of another example of a graphicaluser-interactive representation of an MTU naming and catalog section ofa market-tech unit (MTU) data record of an MTU database;

FIG. 40 is a schematic block diagram of an example of a relationshipbetween CIE (communication, information, and electrical technologies)fundamental hardware (HW) component market-tech units (MTUs), CIE techfundamental HW circuit MTUs, and CIE tech fundamental HW circuit blockMTUs;

FIG. 41 is a schematic block diagram of another example of a graphicaluser interface (GUI) of an improved computer for technology with anentry of cell phone for an MTU name;

FIG. 42A is a schematic block diagram of another example of auser-interactive graphical representation of a market-tech unit (MTU)data record for a cell phone;

FIG. 42B is a schematic block diagram of another example of auser-interactive graphical representation of an MTU naming and catalogsection of a cell phone market-tech unit (MTU) data record;

FIG. 43 is a schematic block diagram of an example of a user-interactivegraphical MTU inclusion functional diagram of a cell phone market-techunit (MTU) data record;

FIG. 44 is a schematic block diagram of an example of a user-interactivegraphical MTU inclusion hierarchy diagram of a cell phone market-techunit (MTU) data record;

FIG. 45 is a schematic block diagram of an example of a user-interactivegraphical MTU composition functional diagram of a cell phone market-techunit (MTU) data record;

FIG. 46 is a schematic block diagram of an example of a user-interactivegraphical MTU composition hierarchy diagram of a cell phone market-techunit (MTU) data record;

FIG. 47 is a schematic block diagram of an example of a user-interactivegraphical general description section of a cell phone market-tech unit(MTU) data record;

FIG. 48 is a schematic block diagram of an example of a user-interactivegraphical MTU synonyms section of a cell phone market-tech unit (MTU)data record;

FIG. 49 is a schematic block diagram of an example of a user-interactivegraphical related MTUs section of a cell phone market-tech unit (MTU)data record;

FIG. 50 is a schematic block diagram of an example of a user-interactivegraphical metadata section of a cell phone market-tech unit (MTU) datarecord;

FIG. 51 is a schematic block diagram of an example of a user-interactivegraphical science categories section of a cell phone market-tech unit(MTU) data record;

FIG. 52 is a schematic block diagram of an example of a user-interactivegraphical manufacturing data section of a cell phone market-tech unit(MTU) data record;

FIG. 53 is a schematic block diagram of an example of a user-interactivegraphical MSBT (marketing, sales, business, and technical) section of amarket-tech unit (MTU) data record;

FIG. 54 is a schematic block diagram of an example of a user-interactivegraphical market impact section of a market-tech unit (MTU) data record;

FIG. 55 is a schematic block diagram of an example of a user-interactivegraphical MTU boundary section of a market-tech unit (MTU) data record;

FIG. 56 is a schematic block diagram of an example of interacting with auser-interactive graphical MTU boundary section of a market-tech unit(MTU) data record;

FIG. 57 is a schematic block diagram of an example of a user-interactivegraphical MTU patent data section of a market-tech unit (MTU) datarecord;

FIG. 58 is a schematic block diagram of another example of interactingwith a user-interactive graphical MTU boundary section of a market-techunit (MTU) data record;

FIG. 59 is a schematic block diagram of an example of interacting with auser-interactive UVP (unique value proposition) to marketable featuresto technology challenges section of a graphical MTU boundary section ofa market-tech unit (MTU) data record;

FIG. 60 is a schematic block diagram of an example of user-interactivegraphical lists of marketable features, UVP (unique value proposition),and technology challenges of a user-interactive UVP to marketablefeatures to technology challenges section of a graphical MTU boundarysection of a cell phone market-tech unit (MTU) data record;

FIG. 61 is a schematic block diagram of an example of a user-interactiveUVP (unique value proposition) to marketable features to technologychallenges diagram of a graphical MTU boundary section of a cell phonemarket-tech unit (MTU) data record;

FIG. 62 is a schematic block diagram of an example of interacting with auser-interactive UVP (unique value proposition) to marketable featuresto technology challenges section of a graphical MTU boundary section ofa market-tech unit (MTU) data record;

FIG. 63 is a schematic block diagram of an example of interacting with auser-interactive technology challenges to problems to inventiveembodiments of a user-interactive UVP to marketable features totechnology challenges section of a graphical MTU boundary section of acell phone market-tech unit (MTU) data record;

FIG. 64 is a schematic block diagram of an example of user-interactivegraphical lists of technology challenges, problems, and inventiveembodiments of a user-interactive UVP to marketable features totechnology challenges section of a graphical MTU boundary section of acell phone market-tech unit (MTU) data record;

FIG. 65 is a schematic block diagram of an example of a user-interactivegraphical representation of technology challenges to problems toinventive concepts to implementation options to solutions to inventiveembodiments relational map;

FIG. 66 is a schematic block diagram of an example of a user-interactivegraphical MTU composition functional diagram of a cell phone market-techunit (MTU) data record;

FIG. 67 is a schematic block diagram of an example of a user-interactivegraphical market-tech unit (MTU) data record for input/output hardware(HW) of a cell phone;

FIG. 68 is a schematic block diagram of an example of a user-interactivegraphical input/output hardware (HW) of a cell phone inclusivefunctional diagram is the same as a user-interactive graphical cellphone composition functional diagram;

FIG. 69 is a schematic block diagram of an example of a user-interactivegraphical input/output hardware (HW) of a cell phone inclusive hierarchydiagram is the same as a user-interactive graphical cell phonecomposition hierarchy diagram;

FIG. 70 is a schematic block diagram of an example of a user-interactivegraphical input/output hardware (HW) of a cell phone compositionfunctional diagram;

FIG. 71 is a schematic block diagram of an example of a user-interactivegraphical input/output hardware (HW) of a cell phone compositionhierarchy diagram;

FIG. 72 is a schematic block diagram of an example of a user-interactivegraphical MTU naming & catalog section of a market-tech unit (MTU) datarecord for input/output hardware (HW) of a cell phone;

FIG. 73 is a schematic block diagram of an example of a user-interactivegraphical cell phone composition functional diagram with “tier −2”details;

FIG. 74 is a schematic block diagram of an example of a user-interactivegraphical market-tech unit (MTU) data record for a touch screen ofinput/output hardware (HW) of a cell phone;

FIG. 75 is a schematic block diagram of an example of a user-interactivegraphical composition functional diagram of a touch screen ofinput/output hardware (HW) of a cell phone;

FIG. 76 is a schematic block diagram of an example of a user-interactivegraphical MTU naming & catalog section of a market-tech unit (MTU) datarecord for a touch screen of input/output hardware (HW) of a cell phone;

FIG. 77 is a schematic block diagram of an example of a user-interactivegraphical market-tech unit (MTU) data record for a touch screencontroller of a touch screen of input/output hardware (HW) of a cellphone;

FIG. 78 is a schematic block diagram of an example of a user-interactivegraphical composition functional diagram of a touch screen controller ofa touch screen of input/output hardware (HW) of a cell phone;

FIG. 79 is a schematic block diagram of an example of a user-interactivegraphical MTU naming & catalog section of a market-tech unit (MTU) datarecord for a touch screen controller of a touch screen of input/outputhardware (HW) of a cell phone;

FIG. 80 is a schematic block diagram of an example of a user-interactivegraphical composition functional diagram of a touch screen ofinput/output hardware (HW) of a cell phone with “tier −2” details;

FIG. 81 is a schematic block diagram of an example of a user-interactivegraphical market-tech unit (MTU) data record for a sensor circuit of atouch screen controller of a touch screen of input/output hardware (HW)of a cell phone;

FIG. 82 is a schematic block diagram of an example of a user-interactivegraphical composition functional diagram of a sensor circuit of a touchscreen controller of a touch screen of input/output hardware (HW) of acell phone;

FIG. 83 is a schematic block diagram of an example of a user-interactivegraphical MTU naming & catalog section of a market-tech unit (MTU) datarecord for a sensor circuit of a touch screen controller of a touchscreen of input/output hardware (HW) of a cell phone;

FIG. 84 is a schematic block diagram of an example of a user-interactivegraphical market-tech unit (MTU) data record for a sense circuit of asensor circuit of a touch screen controller of a touch screen ofinput/output hardware (HW) of a cell phone;

FIG. 85 is a schematic block diagram of an example of a user-interactivegraphical composition functional diagram of a sense circuit of a sensorcircuit of a touch screen controller of a touch screen of input/outputhardware (HW) of a cell phone;

FIG. 86 is a schematic block diagram of an example of a user-interactivegraphical MTU naming & catalog section of a market-tech unit (MTU) datarecord for a sense circuit of a sensor circuit of a touch screencontroller of a touch screen of input/output hardware (HW) of a cellphone;

FIG. 87 is a schematic block diagram of an example of a user-interactivegraphical composition functional diagram of a sensor circuit of a touchscreen of input/output hardware (HW) of a cell phone with “tier −2”details;

FIG. 88 is a schematic block diagram of an example of a user-interactivegraphical market-tech unit (MTU) data record for an analog to digitalconverter;

FIG. 89 is a schematic block diagram of an example of a user-interactivegraphical composition functional diagram of an analog to digitalconverter;

FIG. 90 is a schematic block diagram of an example of a user-interactivegraphical MTU naming & catalog section of a market-tech unit (MTU) datarecord for an analog to digital converter, which is a fundamental MTU;

FIG. 91 is a schematic block diagram of an example of a user-interactivegraphical market-tech unit (MTU) data records for MTUs related to thesense circuit of a sensor circuit of a touch screen controller of atouch screen of input/output hardware (HW) of a cell phone;

FIG. 92 is a schematic block diagram of an example of a user-interactivegraphical market-tech unit (MTU) data record for a sense circuit of asensor circuit of a touch screen controller of a touch screen ofinput/output hardware (HW) of a cell phone that includes related MTUinclusions of the sensor circuit;

FIG. 93 is a schematic block diagram of an example of a user-interactivegraphical composition functional diagram of expanded use of a touchscreen;

FIG. 94A is a schematic block diagram of a sensor circuit driving andsensing a sensor;

FIG. 94B is a schematic block diagram of an example of auser-interactive graphical composition diagram of tech challenge toinventive embodiments for a sensor circuit;

FIG. 95 is a medial side view diagram of a shoe;

FIG. 96 is an isometric diagram of a force transferring sole for theshoe of FIG. 95 ;

FIG. 97 is a schematic block diagram of an example of a user-interactivegraphical market-tech unit (MTU) hierarchy diagram for footwear;

FIG. 98 is a schematic block diagram of an example of mapping an initialinventive embodiment of the sole of FIG. 96 to the user-interactivegraphical market-tech unit (MTU) hierarchy diagram for footwear of FIG.97 ;

FIG. 99 is a schematic block diagram of an example of expanding theinitial inventive embodiment mapping of FIG. 98 of midsoles of baseballshoes to further insoles and outsoles of baseball shoes;

FIG. 100 is a schematic block diagram of an example of further expandingthe inventive embodiment mapping of FIG. 99 of insole, midsoles, andoutsoles of baseball shoes to insoles, midsoles, and outsoles of otherathletic shoes;

FIG. 101 is a schematic block diagram of an example of further expandingthe inventive embodiment mapping of FIG. 100 of all athletic shoes toother types of shoes;

FIG. 102 is a schematic block diagram of an example of further expandingthe inventive embodiment mapping of FIG. 101 of almost all shoes toother types of products worn on the feet;

FIG. 103 is a schematic block diagram of an example of auser-interactive graphical composition diagram of tech challenge toinventive embodiments for sole FT concept for use as mapped in FIG. 102;

FIG. 104 is a schematic block diagram of a further example of auser-interactive graphical composition diagram of tech challenge toinventive embodiments for sole FT concept for use as mapped in FIG. 102;

FIG. 105 is a schematic block diagram of a further example of auser-interactive graphical composition diagram of tech challenge toinventive embodiments for sole FT concept for use as mapped in FIG. 102;

FIG. 106 is a schematic block diagram of a further example of auser-interactive graphical composition diagram of tech challenge toinventive embodiments for sole FT concept for use as mapped in FIG. 102;

FIG. 107 is a schematic block diagram of an example of the data thatcomprises a market-tech unit (MTU) data record in an MTU database;

FIG. 108 is a schematic block diagram of another embodiment of animproved computer for technology;

FIG. 109 is a schematic block diagram of an embodiment of an MSBTP(marketing, sales, business, technology, and patent) data gatheringsection of an improved computer for technology;

FIG. 110 is a schematic block diagram of an example of characteristicsof MSBT (marketing, sales, business, & technology) data ingested by theimproved computer for technology;

FIG. 111 is a schematic block diagram of a further embodiment of anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology;

FIG. 112 is a schematic block diagram of an example of a userinteractive graphical MSBT (marketing, sales, business, & technology)data record of an MSBT database of the improved computer for technology;

FIG. 113 is a schematic block diagram of an example of characteristicsof patent data ingested by the improved computer for technology;

FIG. 114 is a schematic block diagram of a further embodiment of anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology;

FIG. 115 is a schematic block diagram of an example of a userinteractive graphical annotated patent data record of an annotatedpatent database of the improved computer for technology;

FIG. 116 is a schematic block diagram of an example of a userinteractive graphical annotated patent term record of a patent termdatabase of the improved computer for technology;

FIG. 117 is a schematic block diagram of a further embodiment of anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology;

FIG. 118 is a schematic block diagram of a further embodiment of anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology;

FIG. 119 is a schematic block diagram of a further embodiment of anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology;

FIG. 120 is a schematic block diagram of an embodiment of a subscriptionbased user interface section, subscription pricing, and market impactsection of an improved computer for technology;

FIG. 121 is a schematic block diagram of a further embodiment of amarket impact section of an improved computer for technology;

FIG. 122 is a schematic block diagram of an example of a userinteractive graphical market impact of an MTU record of a market impact(MI) database of the improved computer for technology;

FIG. 123 is a schematic block diagram of a further embodiment of anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology;

FIG. 124 is a logic diagram of an example of ingesting MSBT documents byan MSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology;

FIG. 125 is a logic diagram of another example of ingesting MSBTdocuments by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technology;

FIG. 126 is a logic diagram of another example of ingesting MSBTdocuments by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technology;

FIGS. 127A through 127D are a logic diagram of another example ofingesting MSBT documents by an MSBTP (marketing, sales, business,technology, and patent) data gathering section of an improved computerfor technology;

FIGS. 128A through 128C are a logic diagram of another example ofingesting MSBT documents by an MSBTP (marketing, sales, business,technology, and patent) data gathering section of an improved computerfor technology;

FIGS. 129A through 129F are diagrams of other examples of ingesting MSBTdocuments by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technology;

FIGS. 130A and 130B are a logic diagram of another example of ingestingMSBT documents by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technology;

FIG. 131 is a logic diagram of another example of ingesting MSBTdocuments by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technology;

FIG. 132 is a logic diagram of another example of ingesting MSBTdocuments by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technology;

FIG. 133 is a diagram of another example of ingesting a datasheet by anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology;

FIG. 134 is a logic diagram of another example of ingesting MSBTdocuments by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technology;

FIG. 135 is a diagram of another example of document partitioning by anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology;

FIG. 136 is a logic diagram of another example of ingesting MSBTdocuments by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technology;

FIG. 137 is a diagram of an example of MTU tagging a document by anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology;

FIG. 138 is a diagram of another example of MTU tagging a document by anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology;

FIGS. 139A through 139D are diagrams of examples regarding MTU tagging adocument by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technology;

FIG. 140 is a logic diagram of an example of a method for MTU tagging adocument by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technology;

FIG. 141 is a logic diagram of an example of a method for generating anew MSBT data record for an MSBT document by an MSBTP (marketing, sales,business, technology, and patent) data gathering section of an improvedcomputer for technology;

FIG. 142 is a schematic block diagram of a further embodiment of anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology;

FIG. 143 is a schematic block diagram of a further embodiment of anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology regardingingesting patents and patent applications;

FIGS. 144A through 144G are a logic diagram of an example of a methodfor ingesting patents and patent applications by an MSBTP (marketing,sales, business, technology, and patent) data gathering section of animproved computer for technology;

FIG. 145 is a logic diagram of an example of a method for generating anew annotated patent record for an MSBT document by an MSBTP (marketing,sales, business, technology, and patent) data gathering section of animproved computer for technology;

FIG. 146 is a logic diagram of an example of a method for generating anew patent term record for an MSBT document by an MSBTP (marketing,sales, business, technology, and patent) data gathering section of animproved computer for technology;

FIG. 147 is a logic diagram of an example of a method for identifying anew market-tech unit (MTU) by an MSBTP (marketing, sales, business,technology, and patent) data gathering section of an improved computerfor technology;

FIG. 148 is a logic diagram of an example of a method forgenerating/updating a market-tech unit (MTU) composition diagram by anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology;

FIG. 149 is a logic diagram of an example of a method forgenerating/updating a market-tech unit (MTU) composition diagram by anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology;

FIGS. 150A through 150C are a logic diagram of an example of a methodfor generating/updating a market-tech unit (MTU) symbol by an MSBTP(marketing, sales, business, technology, and patent) data gatheringsection of an improved computer for technology;

FIG. 151 is a schematic block diagram of a further embodiment of animproved computer for technology regarding use of MTU data records;

FIG. 152 is a schematic block diagram of a further embodiment of animproved computer for technology;

FIG. 153 is a logic diagram of an example of a method for accessing amarket-tech unit (MTU) record from an MTU database by an MTU operatingsystem of an improved computer for technology;

FIG. 154 is a schematic block diagram of a further embodiment of animproved computer for technology regarding generating of an existingpatent landscape report for an MTU;

FIG. 155 is a schematic block diagram of a further embodiment of animproved computer for technology regarding generating of an existingmarket impact report for an MTU;

FIG. 156 is a schematic block diagram of a further embodiment of animproved computer for technology regarding generating of a reportregarding how well an MTU is protected by existing patents and existinginventions;

FIG. 157 is a schematic block diagram of a further embodiment of animproved computer for technology regarding generating of a reportregarding value of an MTU based on existing patents and inventionsreports;

FIG. 158 is a schematic block diagram of a further embodiment of animproved computer for technology regarding generating of a forecastedfuture patent landscape report for an MTU;

FIG. 159 is a schematic block diagram of a further embodiment of animproved computer for technology regarding generating of a forecastedfuture market impact report for an MTU;

FIG. 160 is a schematic block diagram of a further embodiment of animproved computer for technology regarding generating of a reportregarding how well an MTU is protected by forecasted future patents andexisting inventions;

FIG. 161 is a schematic block diagram of a further embodiment of animproved computer for technology regarding generating of a reportregarding value of an MTU based on existing patents and inventionsreports;

FIG. 162 is a schematic block diagram of an example of interactionbetween a patent plan and a budget as processed by an improved computerfor technology;

FIG. 163 is a diagram of an example of fees associated with patentprotecting an MTU as used by the improved computer for technology;

FIG. 164 is a logic diagram of an example of a method for balancingpatent spend and desired patent position for a plan to patent protect anMTU (market-tech unit) by a growth and expense co-processor of animproved computer for technology;

FIG. 165 is a diagram of an example of an input record regarding expenseand growth of patent protecting an MTU as used by a growth and expenseco-processor of an improved computer for technology;

FIG. 166 is a diagram of another example of an input record regardingexpense and growth of patent protecting an MTU as used by a growth andexpense co-processor of an improved computer for technology;

FIG. 167 is a logic diagram of another example of a method for balancingpatent spend and desired patent position for a plan to patent protect anMTU (market-tech unit) by a growth and expense co-processor of animproved computer for technology;

FIG. 168 is a diagram of another example of an input record regardingexpense and growth of patent protecting an MTU as used by a growth andexpense co-processor of an improved computer for technology;

FIG. 169 is a diagram of another example of an input record regardingexpense and growth of patent protecting an MTU as used by a growth andexpense co-processor of an improved computer for technology;

FIG. 170 is a diagram of an example of a multi-period expense and growthestimation of patent protecting an MTU that compounds over time;

FIG. 171 is a diagram of an example of a multiple time periodsrelationship to each other as time passes regarding expense and growthestimation of patent protecting an MTU;

FIG. 172 is a diagram of an example of a growth forecast recordregarding patent protecting an MTU as used by a growth and expenseco-processor of an improved computer for technology;

FIG. 173 is a diagram of another example of a growth forecast recordregarding patent protecting an MTU as used by a growth and expenseco-processor of an improved computer for technology;

FIG. 174 is a diagram of another example of a growth forecast recordregarding patent protecting an MTU as used by a growth and expenseco-processor of an improved computer for technology;

FIG. 175 is a logic diagram of an example of a method for forecastingupcoming actions regarding patent protecting an MTU (market-tech unit)based on existing patent protected inventions by a growth and expenseco-processor of an improved computer for technology;

FIG. 176 is a logic diagram of an example of a method for forecastingupcoming actions regarding patent protecting an MTU (market-tech unit)based on patent protected inventions of the current period by a growthand expense co-processor of an improved computer for technology;

FIG. 177 is a logic diagram of an example of a method for forecastingupcoming actions regarding patent protecting an MTU (market-tech unit)based on patent protected inventions of the 1^(st) next period by agrowth and expense co-processor of an improved computer for technology;

FIG. 178 is a logic diagram of an example of a method for forecastingupcoming actions regarding patent protecting an MTU (market-tech unit)based on patent protected inventions of the 2^(nd) next period by agrowth and expense co-processor of an improved computer for technology;

FIG. 179 is a logic diagram of an example of a method for forecastingupcoming actions regarding patent protecting an MTU (market-tech unit)based on patent protected inventions of the 3^(rd) next period by agrowth and expense co-processor of an improved computer for technology;

FIG. 180 is a logic diagram of an example of a method for forecastingupcoming actions regarding patent protecting an MTU (market-tech unit)based on patent protected inventions of the 4^(th) next period by agrowth and expense co-processor of an improved computer for technology;

FIG. 181 is a logic diagram of an example of a method for forecastingupcoming actions regarding patent protecting an MTU (market-tech unit)based on patent protected inventions of the 5^(th) next period by agrowth and expense co-processor of an improved computer for technology;

FIG. 182 is a logic diagram of an example of a method for forecastingupcoming actions regarding patent protecting an MTU (market-tech unit)based on patent protected inventions of the n^(th) next period by agrowth and expense co-processor of an improved computer for technology;

FIG. 183 is a logic diagram of an example of a method for combiningactions regarding patent protecting an MTU (market-tech unit) that areforecasted to occur in the current period by a growth and expenseco-processor of an improved computer for technology;

FIG. 184 is a logic diagram of an example of a method for combiningactions regarding patent protecting an MTU (market-tech unit) that areforecasted to occur in the 1^(st) next period by a growth and expenseco-processor of an improved computer for technology;

FIG. 185 is a logic diagram of an example of a method for combiningactions regarding patent protecting an MTU (market-tech unit) that areforecasted to occur in the 2^(nd) next period by a growth and expenseco-processor of an improved computer for technology;

FIG. 186 is a logic diagram of an example of a method for combiningactions regarding patent protecting an MTU (market-tech unit) that areforecasted to occur in the 3^(rd) next period by a growth and expenseco-processor of an improved computer for technology;

FIG. 187 is a logic diagram of an example of a method for combiningactions regarding patent protecting an MTU (market-tech unit) that areforecasted to occur in the 4^(th) next period by a growth and expenseco-processor of an improved computer for technology;

FIG. 188 is a logic diagram of an example of a method for combiningactions regarding patent protecting an MTU (market-tech unit) that areforecasted to occur in the 5^(th) next period by a growth and expenseco-processor of an improved computer for technology;

FIG. 189 is a logic diagram of an example of a method for combiningactions regarding patent protecting an MTU (market-tech unit) that areforecasted to occur in the 6^(th) next period by a growth and expenseco-processor of an improved computer for technology;

FIG. 190 is a logic diagram of an example of a method for combining USand international actions regarding patent protecting multiple MTUs(market-tech units) that are forecasted to occur in the current periodby a growth and expense co-processor of an improved computer fortechnology;

FIG. 191 is a logic diagram of an example of a method for combining USand international actions regarding patent protecting multiple MTUs(market-tech units) that are forecasted to occur in the 1^(st) nextperiod by a growth and expense co-processor of an improved computer fortechnology;

FIG. 192 is a logic diagram of an example of a method for combining USand international actions regarding patent protecting multiple MTUs(market-tech units) that are forecasted to occur in the 2^(nd) nextperiod by a growth and expense co-processor of an improved computer fortechnology;

FIG. 193 is a logic diagram of an example of a method for combining USand international actions regarding patent protecting multiple MTUs(market-tech units) that are forecasted to occur in the 3^(rd) nextperiod by a growth and expense co-processor of an improved computer fortechnology;

FIG. 194 is a logic diagram of an example of a method for combining USand international actions regarding patent protecting multiple MTUs(market-tech units) that are forecasted to occur in the 4^(th) nextperiod by a growth and expense co-processor of an improved computer fortechnology;

FIG. 195 is a logic diagram of an example of a method for combining USand international actions regarding patent protecting multiple MTUs(market-tech units) that are forecasted to occur in the 5^(th) nextperiod by a growth and expense co-processor of an improved computer fortechnology;

FIG. 196 is a logic diagram of an example of a method for combining USand international actions regarding patent protecting multiple MTUs(market-tech units) that are forecasted to occur in the 6^(th) nextperiod by a growth and expense co-processor of an improved computer fortechnology;

FIG. 197 is a logic diagram of an example of a method for forecastingnew inventions per period to patent protect for an MTU (market-techunit) by a growth and expense co-processor of an improved computer fortechnology;

FIG. 198 is a logic diagram of another example of a method forforecasting new inventions per period to patent protect for an MTU(market-tech unit) by a growth and expense co-processor of an improvedcomputer for technology;

FIG. 199 is a diagram of an example of relative total number ofinventions, ideal number of inventions, and desired number of inventionsto protect for an MTU (market-tech unit) over the life of the MTU;

FIG. 200 is a diagram of another example of relative total number ofinventions, ideal number of inventions, and desired number of inventionsto protect for an MTU (market-tech unit) over the life of the MTU ifpatent protecting inventions started late the deploy phase;

FIG. 201 is a diagram of an example of a prosecution forecasting timingwindows for a patent application filed in the current period as used bya growth and expense co-processor of an improved computer fortechnology;

FIG. 202 is a diagram of an example of prosecution forecastingparameters as determined and used by a growth and expense co-processorof an improved computer for technology;

FIG. 203 is a diagram of an example of prosecution forecasting timingwindows for a first patent application filed in the current period basedon the timing windows of FIG. 201 ;

FIG. 204 is a diagram of an example of forecasted probabilities of whenoffice actions for the first patent application will be received asdetermined by a growth and expense co-processor of an improved computerfor technology;

FIG. 205 is a diagram of an example of forecasted probabilities of whenoffice actions will be received combined with the forecastedprobabilities of receiving office actions for the first patentapplication as determined by a growth and expense co-processor of animproved computer for technology;

FIG. 206 is a diagram of an example of prosecution forecasting timingwindows for a second patent application having the first office actionwindow within the current period;

FIG. 207 is a diagram of an example of forecasted probabilities of whenoffice actions for the second patent application will be received asdetermined by a growth and expense co-processor of an improved computerfor technology based on the timing of FIG. 206 ;

FIG. 208 is a diagram of an example of forecasted probabilities of whenoffice actions will be received combined with the forecastedprobabilities of receiving office actions for the second patentapplication as determined by a growth and expense co-processor of animproved computer for technology;

FIG. 209 is a diagram of an example of prosecution forecasting timingwindows for a patent application having the second office action windowbeing open in the first and second next periods and response to thefirst office action was filed during the current period;

FIG. 210 is a diagram of an example of updated prosecution forecastingparameters as determined and used by a growth and expense co-processorof an improved computer for technology based on the timing of FIG. 209 ;

FIG. 211 is a diagram of an example of prosecution forecasting timingwindows for a third patent application having the second office actionwindow being open in the first and second next periods and response tothe first office action was filed during the current period;

FIG. 212 is a diagram of an example of forecasted probabilities of whenoffice actions for the third patent application will be received asdetermined by a growth and expense co-processor of an improved computerfor technology;

FIG. 213 is a diagram of an example of forecasted probabilities of whenoffice actions will be received combined with the forecastedprobabilities of receiving office actions for the third patentapplication as determined by a growth and expense co-processor of animproved computer for technology;

FIG. 214 is a diagram of an example of prosecution forecasting timingwindows for a patent application that is forecasted to be filed in thefirst next period;

FIG. 215 is a diagram of an example of updated prosecution forecastingparameters as determined and used by a growth and expense co-processorof an improved computer for technology based on the timing of FIG. 214 ;

FIG. 216 is a diagram of an example of prosecution forecasting timingwindows for a fourth patent application that is forecasted to be filedin the first next period;

FIG. 217 is a diagram of an example of forecasted probabilities of whenoffice actions for the fourth patent application will be received asdetermined by a growth and expense co-processor of an improved computerfor technology;

FIG. 218 is a diagram of an example of forecasted probabilities of whenoffice actions will be received combined with the forecastedprobabilities of receiving office actions for the fourth patentapplication as determined by a growth and expense co-processor of animproved computer for technology;

FIG. 219 is a diagram of an example of combining the prosecutionforecasting of the first through fourth patent applications asdetermined by a growth and expense co-processor of an improved computerfor technology;

FIG. 220 is a diagram of an example of forecasting the quantity and timeof receiving offices action for the first through fourth patentapplications received per period as determined by a growth and expenseco-processor of an improved computer for technology;

FIG. 221 is a diagram of an example of forecasting first office actionallowances and non-allowance office actions for the first through fourthpatent applications received per period as determined by a growth andexpense co-processor of an improved computer for technology;

FIG. 222 is a diagram of an example of forecasting expense for the firstoffice action allowances and non-allowance office actions of FIG. 221 asdetermined by a growth and expense co-processor of an improved computerfor technology;

FIG. 223 is a diagram of an example of issuance forecasting timingwindows for a patent application that is to be filed in the currentperiod;

FIG. 224 is a diagram of an example of issuance forecasting parametersas determined and used by a growth and expense co-processor of animproved computer for technology based on the timing of FIG. 223 ;

FIG. 225 is a diagram of an example of issuance forecasting timingwindows for a first patent application that is forecasted to be filed inthe current period;

FIG. 226 is a diagram of an example of forecasted probabilities of whena notice of allowance for the first patent application will be receivedas determined by a growth and expense co-processor of an improvedcomputer for technology;

FIG. 227 is a diagram of an example of forecasted probabilities of whena notice of allowance will be received combined with the forecastedprobabilities of receiving a notice of allowance for the first patentapplication as determined by a growth and expense co-processor of animproved computer for technology;

FIG. 228 is a diagram of an example of issuance forecasting timingwindows for a patent application forecasted to receive a first officeaction in the current period;

FIG. 229 is a diagram of an example of issuance forecasting parametersas determined and used by a growth and expense co-processor of animproved computer for technology based on the timing of FIG. 228 ;

FIG. 230 is a diagram of an example of issuance forecasting timingwindows for a second patent application that is forecasted to receive afirst office action in the current period;

FIG. 231 is a diagram of an example of forecasted probabilities of whena notice of allowance for the second patent application will be receivedas determined by a growth and expense co-processor of an improvedcomputer for technology;

FIG. 232 is a diagram of an example of forecasted probabilities of whena notice of allowance will be received combined with the forecastedprobabilities of receiving a notice of allowance for the second patentapplication as determined by a growth and expense co-processor of animproved computer for technology;

FIG. 233 is a diagram of an example of issuance forecasting timingwindows for a patent application forecasted to receive a second officeaction in the 1^(st) next period;

FIG. 234 is a diagram of an example of issuance forecasting parametersas determined and used by a growth and expense co-processor of animproved computer for technology based on the timing of FIG. 233 ;

FIG. 235 is a diagram of an example of issuance forecasting timingwindows for a third patent application that is forecasted to receive asecond office action in the first next period;

FIG. 236 is a diagram of an example of forecasted probabilities of whena notice of allowance for the third patent application will be receivedas determined by a growth and expense co-processor of an improvedcomputer for technology;

FIG. 237 is a diagram of an example of forecasted probabilities of whena notice of allowance will be received combined with the forecastedprobabilities of receiving a notice of allowance for the third patentapplication as determined by a growth and expense co-processor of animproved computer for technology;

FIG. 238 is a diagram of an example of issuance forecasting timingwindows for a patent application forecasted to be filed in the 1^(st)next period;

FIG. 239 is a diagram of an example of issuance forecasting parametersas determined and used by a growth and expense co-processor of animproved computer for technology based on the timing of FIG. 233 ;

FIG. 240 is a diagram of an example of issuance forecasting timingwindows for a fourth patent application that is forecasted to be filedin the first next period;

FIG. 241 is a diagram of an example of forecasted probabilities of whena notice of allowance for the fourth patent application will be receivedas determined by a growth and expense co-processor of an improvedcomputer for technology;

FIG. 242 is a diagram of an example of forecasted probabilities of whena notice of allowance will be received combined with the forecastedprobabilities of receiving a notice of allowance for the fourth patentapplication as determined by a growth and expense co-processor of animproved computer for technology;

FIG. 243 is a diagram of an example of combining issuance forecastingprobabilities and timing for the four example patent applications asdetermined by a growth and expense co-processor of an improved computerfor technology;

FIG. 244 is a diagram of an example of calculating expenses for theissuance forecasting probabilities and timing for the four examplepatent applications as determined by a growth and expense co-processorof an improved computer for technology;

FIG. 245 is a logic diagram of an example of method for forecastingsubsequent filing probabilities and timing as executed by a growth andexpense co-processor of an improved computer for technology;

FIG. 246 is a logic diagram of another example of method for forecastingsubsequent filing probabilities and timing as executed by a growth andexpense co-processor of an improved computer for technology;

FIG. 247 is a diagram of an example of primary and secondary subsequentfiling forecasting parameters for a first patent application asdetermined by a growth and expense co-processor of an improved computerfor technology;

FIG. 248 is a diagram of an example of forecasted probabilities andtiming of a subsequent filing for a first patent application asdetermined by a growth and expense co-processor of an improved computerfor technology;

FIG. 249 is a diagram of an example of primary and secondary subsequentfiling forecasting parameters for a second patent application asdetermined by a growth and expense co-processor of an improved computerfor technology;

FIG. 250 is a diagram of an example of forecasted probabilities andtiming of a subsequent filing for a second patent application asdetermined by a growth and expense co-processor of an improved computerfor technology;

FIG. 251 is a diagram of an example of primary and secondary subsequentfiling forecasting parameters for a third patent application asdetermined by a growth and expense co-processor of an improved computerfor technology;

FIG. 252 is a diagram of an example of forecasted probabilities andtiming of a subsequent filing for a third patent application asdetermined by a growth and expense co-processor of an improved computerfor technology;

FIG. 253 is a diagram of an example of primary and secondary subsequentfiling forecasting parameters for a fourth patent application asdetermined by a growth and expense co-processor of an improved computerfor technology;

FIG. 254 is a diagram of an example of forecasted probabilities andtiming of a subsequent filing for a fourth patent application asdetermined by a growth and expense co-processor of an improved computerfor technology;

FIG. 255 is a diagram of an example of forecasted probabilities andtiming of a filing continuation (CON) patent application for each of thefour patent applications as determined by a growth and expenseco-processor of an improved computer for technology;

FIG. 256 is a diagram of an example of forecasted probabilities andtiming of a filing divisional (DIV) patent application for each of thefour patent applications as determined by a growth and expenseco-processor of an improved computer for technology;

FIG. 257 is a diagram of an example of forecasted probabilities andtiming of a filing continuation-in-part (CIP) patent application foreach of the four patent applications as determined by a growth andexpense co-processor of an improved computer for technology;

FIG. 258 is a diagram of an example of forecasted probabilities andtiming of a filing legal placeholder conversion (LPC) patent applicationfor each of the four patent applications as determined by a growth andexpense co-processor of an improved computer for technology;

FIG. 259 is a diagram of an example of forecasted probabilities andtiming of receiving office actions, receiving notices of allowance, andof filing subsequent patent applications relating to an MTU asdetermined by a growth and expense co-processor of an improved computerfor technology;

FIG. 260 is a diagram of an example of forecasted probabilities andtiming of receiving office actions, receiving notices of allowance, andof filing subsequent patent applications for a plurality of MTUs in theU.S. and in other countries of interest as determined by a growth andexpense co-processor of an improved computer for technology;

FIG. 261 is a schematic block diagram of an example of creating anarchitectural patent protection plan by an improved computer fortechnology;

FIG. 262 is a schematic block diagram of another embodiment of an MTUportfolio creation tool as performed by a co-processor of an improvedcomputer for technology;

FIG. 263 is a schematic block diagram of an embodiment of MTU patentlandscape and competitor analysis units of an improved computer fortechnology;

FIG. 264 is a schematic block diagram of an example of data used by MTUpatent landscape and competitor analysis units of an improved computerfor technology;

FIG. 265 is a diagram of an example of data used by an MTU patentplanning unit and MTU patent landscape and competitor analysis units ofan improved computer for technology;

FIG. 266 is a logic diagram of an example of a method for balance ofpatent spend and desired patent position to produce a multi-year plan topatent protect an MTU as performed by a co-processor of an improvedcomputer for technology;

FIG. 267 is a diagram of an example of value of an MTU based on level ofpatent protection as determined by a co-processor of an improvedcomputer for technology;

FIG. 268 is a logic diagram of an example of a method for determiningpatent position for an MTU as performed by a co-processor of an improvedcomputer for technology;

FIGS. 269A through 269D are S-curve diagrams for an MTU regardingperformance, profitability, number of total inventions, and breadth ofinventions as used by and/or determined by a co-processor of an improvedcomputer for technology;

FIGS. 270A and 270B are S-curve diagrams for an MTU regarding number oftotal inventions and breadth of inventions with an overlay of inventiontypes as used by and/or determined by a co-processor of an improvedcomputer for technology;

FIG. 271 is an S-curve diagram for three generations of an MTU regardingperformance as used by and/or determined by a co-processor of animproved computer for technology;

FIG. 272A is a diagram of an example of relative value of a patent andpatent application regarding a pharmaceutical MTU over time as used byand/or determined by a co-processor of an improved computer fortechnology;

FIG. 272B is a diagram of an example of relative value of a patent andpatent application regarding a communication, information, and/orelectrical technology MTU over time as used by and/or determined by aco-processor of an improved computer for technology;

FIG. 273 is a diagram of an example of relative value of a patent andpatent application regarding an MTU based on a ratio of pending patentapplications to issued patents as used by and/or determined by aco-processor of an improved computer for technology;

FIG. 274 is a diagram of an example of relative value of a patent andpatent application regarding an MTU based on market adoption as used byand/or determined by a co-processor of an improved computer fortechnology;

FIG. 275 is a diagram of an example of timing of a patent applicationand patent regarding an MTU as used by and/or determined by aco-processor of an improved computer for technology;

FIG. 276 is a diagram of an example of a well balance and high qualitypatent portfolio using a fence analogy as would be produced by aco-processor of an improved computer for technology;

FIG. 277 is a diagram of an example of an imbalanced and varying qualitypatent portfolio using a fence analogy as would be produced by aconventional patent process;

FIG. 278 is a diagram of an example of a weak patent portfolio using afence analogy as would be produced by a small company using aconventional patent process;

FIG. 279 is a diagram of an example of an imbalanced and varying qualitypatent portfolio using a fence analogy as would be produced by a largecompany using a conventional patent process;

FIG. 280 is a diagram of another example of a well balance and highquality patent portfolio for an MTU using a fence analogy as would beproduced by a co-processor of an improved computer for technology;

FIG. 281 is a diagram of another example of a well balance and highquality patent portfolio using a fence analogy as would be produced by aco-processor of an improved computer for technology;

FIG. 282 is a diagram of another example of a well balance and highquality patent portfolio using a fence analogy as would be produced by aco-processor of an improved computer for technology;

FIG. 283 is a diagram of another example of a well balance and highquality patent portfolio using a fence analogy as would be produced by aco-processor of an improved computer for technology;

FIG. 284 is a diagram of another example of a well balance and highquality patent portfolio for an MTU using a fence analogy as would beproduced by a co-processor of an improved computer for technology;

FIG. 285 is a diagram of an example of relative total number ofinventions and an ideal number of inventions for an MTU that providedata points for a well balance and high quality patent portfolio aswould be produced by a co-processor of an improved computer fortechnology;

FIG. 286 is a diagram of another example of relative total number ofinventions and an ideal number of inventions for an MTU that providedata points for a well balance and high quality patent portfolio aswould be produced by a co-processor of an improved computer fortechnology;

FIG. 287 is a diagram of an example of invention type quantity andtiming for inventions of an MTU that provide data points for a wellbalance and high quality patent portfolio as would be produced by aco-processor of an improved computer for technology;

FIG. 288 is a diagram of another example of invention type quantity andtiming for inventions of an MTU that provide data points for a wellbalance and high quality patent portfolio as would be produced by aco-processor of an improved computer for technology;

FIG. 289 is a diagram of an example of expanding inventions of a techchallenge associated with an MTU that provide data points for a wellbalance and high quality patent portfolio as would be produced by aco-processor of an improved computer for technology;

FIG. 290 is a diagram of an example of a graph that plots how well anMTU is patent protected with respect to its value as used by and/ordetermined by a co-processor of an improved computer for technology;

FIG. 291 is a diagram of an example of a graph that plots various levelsof how well an MTU is patent protected with respect to its value as usedby and/or determined by a co-processor of an improved computer fortechnology;

FIG. 292 is a diagram of another example of invention type quantity andtiming for inventions of an MTU that provide data points for a wellbalance and high quality patent portfolio as would be produced by aco-processor of an improved computer for technology;

FIG. 293 is a diagram of an example of relative use weighting of variousinvention types as used by and/or determined by a co-processor of animproved computer for technology;

FIG. 294 is a diagram of another example of invention type quantity andtiming for inventions of an MTU that provide data points for a wellbalance and high quality patent portfolio as would be produced by aco-processor of an improved computer for technology;

FIG. 295 is a diagram of another example of invention type quantity andtiming for inventions of an MTU that provide data points for a wellbalance and high quality patent portfolio as would be produced by aco-processor of an improved computer for technology;

FIG. 296 is a diagram of an example of a graph that plots value of anMTU and costs to patent protect the MTU as used by and/or determined bya co-processor of an improved computer for technology;

FIG. 297 is a diagram of an example of a graph that plots an early startof patent protecting a product that includes MTUs with a later start ofpatent protecting the product as used by and/or determined by aco-processor of an improved computer for technology;

FIG. 298 is a diagram of another example of a graph that plots an earlystart of patent protecting an MTU with a later start of patentprotecting the MTU as used by and/or determined by a co-processor of animproved computer for technology;

FIG. 299 is a diagram of another example of a graph that plots an earlystart of patent protecting an MTU with a later start of patentprotecting the MTU as used by and/or determined by a co-processor of animproved computer for technology;

FIG. 300 is a diagram of another example of a graph that plots an earlystart of patent protecting an MTU with a later start of patentprotecting the MTU as used by and/or determined by a co-processor of animproved computer for technology;

FIG. 301 is a diagram of an example of six patent applications issuancerate based on statistics of a conventional patent process;

FIG. 302 is a diagram of an example of expenses for the six patentapplications of FIG. 301 ;

FIG. 303 is a diagram of an example of data for a period of anarchitectural patent protection plan for an MTU as used by and/ordetermined by a co-processor of an improved computer for technology;

FIG. 304 is a diagram of an example of parameter inputs for generating aperiod by period plan for patent protecting an MTU as used by and/ordetermined by a co-processor of an improved computer for technology;

FIG. 305 is a diagram of an example of a period by period plan forpatent protecting an MTU as used by and/or determined by a co-processorof an improved computer for technology;

FIG. 306 is a diagram of an example of a private database record for aninvention of an MTU as used by and/or determined by a co-processor of animproved computer for technology;

FIG. 307 is a diagram of an embodiment of a portfolio valuation tool forvaluing an MTU as performed by a co-processor of an improved computerfor technology;

FIG. 308 is a diagram of an embodiment of data used by a portfoliovaluation tool for valuing an MTU as performed by a co-processor of animproved computer for technology;

FIG. 309 is a diagram of another embodiment of a portfolio valuationtool for valuing an MTU as performed by a co-processor of an improvedcomputer for technology;

FIG. 310 is a diagram of another embodiment of a portfolio valuationtool for valuing an MTU as performed by a co-processor of an improvedcomputer for technology;

FIG. 311 is a diagram of an embodiment of an MTU how well patentprotected co-processor of a portfolio valuation tool for valuing an MTUof an improved computer for technology;

FIG. 312 is a diagram of an embodiment of a portfolio factor score forexiting patents unit and a portfolio factor score for forecasted futurepatents units of a portfolio valuation tool for valuing an MTU of animproved computer for technology;

FIG. 313 is a diagram of another embodiment of a portfolio factor scorefor exiting patents unit of a portfolio valuation tool for valuing anMTU of an improved computer for technology;

FIG. 314 is a diagram of another embodiment of a portfolio factor scorefor forecasted future patents units of a portfolio valuation tool forvaluing an MTU of an improved computer for technology;

FIG. 315 is a diagram of an example of data for a portfolio factor scorefor exiting patents unit of a portfolio valuation tool for valuing anMTU of an improved computer for technology;

FIG. 316 is a diagram of an example of calculated data for a portfoliofactor score for forecasted future patents units of a portfoliovaluation tool for valuing an MTU of an improved computer fortechnology;

FIG. 317 is a diagram of a graph of issued patent percentage to issuedpatent score for valuing an MTU of an improved computer for technology;

FIG. 318 is a diagram of another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology;

FIG. 319 is a diagram of another embodiment of a portfolio factor scorefor exiting patents unit and a portfolio factor score for forecastedfuture patents units of a portfolio valuation tool for valuing an MTU ofan improved computer for technology;

FIG. 320 is a diagram of another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology;

FIG. 321 is a diagram of another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology;

FIG. 322 is a diagram of another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology;

FIGS. 323 and 324 are a diagram of another embodiment of a portfoliofactor score for exiting patents unit and a portfolio factor score forforecasted future patents units of a portfolio valuation tool forvaluing an MTU of an improved computer for technology;

FIG. 325 is a diagram of another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology;

FIG. 326 is a diagram of another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology;

FIG. 327 is a diagram of another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology;

FIGS. 328 and 329 are a diagram of another embodiment of a portfoliofactor score for exiting patents unit and a portfolio factor score forforecasted future patents units of a portfolio valuation tool forvaluing an MTU of an improved computer for technology;

FIG. 330 is a diagram of another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology;

FIG. 331 is a diagram of another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology;

FIG. 332 is a diagram of another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology;

FIGS. 333 through 335 are a diagram of another embodiment of a portfoliofactor score for exiting patents unit and a portfolio factor score forforecasted future patents units of a portfolio valuation tool forvaluing an MTU of an improved computer for technology;

FIG. 336 is a diagram of another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology;

FIG. 337 is a diagram of another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology;

FIG. 338 is a diagram of a graph of pending to issued percentage topending to issued score for valuing an MTU of an improved computer fortechnology;

FIG. 339 is a diagram of an embodiment of an invention scope factorscore for exiting patents unit and an invention factor score forforecasted future patents units of a portfolio valuation tool forvaluing an MTU of an improved computer for technology;

FIGS. 340 through 342 are a diagram of another embodiment of aninvention scope factor score for exiting patents unit and an inventionfactor score for forecasted future patents units of a portfoliovaluation tool for valuing an MTU of an improved computer fortechnology;

FIG. 343 is a diagram of an example of calculated data for an inventionfactor score for forecasted future patents units of a portfoliovaluation tool for valuing an MTU of an improved computer fortechnology;

FIG. 344 is a diagram of a graph of a score to actual to ideal inventionpercentage for valuing an MTU of an improved computer for technology;

FIG. 345 is a diagram of another embodiment of an invention scope factorscore for exiting patents unit and an invention factor score forforecasted future patents units of a portfolio valuation tool forvaluing an MTU of an improved computer for technology;

FIGS. 346 and 347 are a diagram of another embodiment of an inventionscope factor score for exiting patents unit and an invention factorscore for forecasted future patents units of a portfolio valuation toolfor valuing an MTU of an improved computer for technology;

FIG. 348 is a diagram of another example of calculated data for aninvention factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology;

FIG. 349 is a diagram of another example of calculated data for aninvention factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology;

FIG. 350 is a diagram of another example of calculated data for aninvention factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology;

FIGS. 351 and 352 are a diagram of another embodiment of an inventionscope factor score for exiting patents unit and an invention factorscore for forecasted future patents units of a portfolio valuation toolfor valuing an MTU of an improved computer for technology;

FIG. 353 is a diagram of a graph of PG to CG score to CG level ofdisruption for valuing an MTU of an improved computer for technology;

FIG. 354 is a diagram of another embodiment of an ideal number ofinventions unit of an invention scope factor score for exiting patentsunit and of an invention factor score for forecasted future patentsunits of a portfolio valuation tool for valuing an MTU of an improvedcomputer for technology;

FIG. 355 is a diagram of another embodiment of an ideal number ofinventions unit of an invention scope factor score for exiting patentsunit and of an invention factor score for forecasted future patentsunits of a portfolio valuation tool for valuing an MTU of an improvedcomputer for technology;

FIG. 356 is a diagram of another embodiment of an ideal number ofinventions unit of an invention scope factor score for exiting patentsunit and of an invention factor score for forecasted future patentsunits of a portfolio valuation tool for valuing an MTU of an improvedcomputer for technology;

FIG. 357 is a diagram of a graph of UVP traits to time for valuing anMTU of an improved computer for technology;

FIG. 358 is a diagram of another embodiment of an ideal number ofinventions unit of an invention scope factor score for exiting patentsunit and of an invention factor score for forecasted future patentsunits of a portfolio valuation tool for valuing an MTU of an improvedcomputer for technology;

FIG. 359 is a diagram of a graph of generations to time for valuing anMTU of an improved computer for technology;

FIG. 360 is a diagram of a an MTU to inventive embodiment mapping forvaluing an MTU of an improved computer for technology;

FIGS. 361 and 362 are a diagram of an embodiment of a market-patent “k”factor co-processor of a portfolio valuation tool for valuing an MTU ofan improved computer for technology;

FIGS. 363 and 364 are a diagram of an embodiment of patent use toolexecuted by co-processor of an improved computer for technology;

FIG. 365 is a diagram of an embodiment of patent data extraction toolexecuted by co-processor of an improved computer for technology;

FIG. 366 is a diagram of an example of calculated data for a patentquality analysis tool executed by a co-processor of an improved computerfor technology; and

FIG. 367 is a logic diagram of an example of a method for calculatingpatent quality as performed by executed by a co-processor of an improvedcomputer for technology.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1A is a schematic block diagram of an example of a conventionalpatent process that includes four main components: invent & disclose;filing decision; patent application preparation & prosecution; andpatent use. Engineers are primarily responsible for the invent &disclose component; a patent committee is responsible for the filingdecision component; patent attorneys are primarily responsible for thepatent application preparation & prosecution component; and licensing &litigation attorneys are responsible for licensing and litigating issuedpatents.

In addition to the patent uses of licensing and litigating, patents areassets that may be bought, sold, traded (cross-licensed), used ascollateral, used to create a spin-off entity, and/or used in a jointventure. For each type of use, valuing the patents is an important step.This is usually done by damage experts who apply statutory laws and/orcase law to determine a financial model for valuing a patent. Forvaluing a patent portfolio, the calculated value of a few patents isoften extrapolated to estimate the value of the patent portfolio.

Working on product development and/or in research & development (R&D)provide the opportunity for engineers to invent. When an engineerinvents something that they believe is worthy of being patented, theengineer discloses it. The invention disclosure process may be an ad hocprocess (like many small companies use) up to a sophisticatedcomputerized submission process (like many large companies use).

If an engineer is not well versed at recognizing patentable ideas, theyrender their decision to disclose based on whether the idea would begood subject matter for a white paper. With this approach, too manypotentially valuable patentable ideas do not get disclosed.

For most engineers, participating in the patent process is an ancillaryfunction to their primary job. For many, the patent process is asignificant burden and only participate when absolutely necessary. Forinstance, many companies have a mandate for a minimum number ofinvention disclosures per year per engineer. For other engineers, theydo not mind the patent process. As a result, an imbalance of inventiondisclosures are received.

If a company has a patent committee, it is often composed of engineeringmanagement, business unit representatives, and patent attorneys thatmeet regularly (e.g., monthly). The patent committee's responsibility isto render filing decisions on received invention disclosures. On anindividual basis, the patent committee attempts to determine whether aninvention, if patented, would it have value to the business. If theybelieve it would, the decision is to file for patent protection and mayfurther indicate in which countries to seek patent protection.

Patent committees use a variety of decision metrics to render theirdecision. At the forefront of the decision making process is the annualpatent budget, which drives how many new patent applications can befiled in the present year. Other decision metrics include likely use byothers, problem being solved, infringement detectability, andobviousness estimations.

FIG. 1B is a schematic block diagram of an example of an annual budgetfor a conventional patent process. The annual budget is for thepreparation, prosecution, issuance, and maintenance of patents. Ittypically does not include the expenses for using patents. Patent usesoften have their own budget.

An annual patent budget is divided into a U.S. portion and aninternational portion. For large companies that have extensive patentportfolios, the international portion may be more than 50% of the totalannual patent. For smaller companies that have relatively small patentportfolios, the international portion may be 0% to 10% of the totalannual budget.

On the U.S. side, the budget is divided between new patent applicationsand on-going portfolio expenses of prosecution, issuance, maintenance,and subsequent patent application filings. The on-going portfolioexpenses is estimated, and the remaining amount is allocated to newpatent applications. The annual patent budget can be increased ordecreased by adjusting the number of new patent applications.

For larger companies, the number of new patent applications is dividedamong divisions (or departments, groups, business units, sectors, etc.),with each getting an assigned target number. It is these numbers thatthe patent committee factors into their decision. A similar allocationoccurs on the international side.

FIG. 1C is a schematic block diagram of an example of a conventionalpatent process with accompanying components of an annual budget. In thefigure, the annual patent budget drives the workload of patentattorneys. For the most part, a patent attorney writing a new patentapplication or prosecuting a pending patent application does so with afocus of getting this patent application to issue. A good patentattorney will further focus on business use of the patent.

When a patent application is allowed, it's processed for issuance and isfurther reviewed for subsequent filing by the patent committee. Asubsequent filing is a continuation patent application, a divisionalpatent application, or a continuation-in-part patent application. Thepatent committee renders its decision based on the decision metricsdiscussed above, which are annual budget and individual patent driven.If a favorable decision is rendered, a subsequent patent application isprepared and filed.

FIG. 1D is a schematic block diagram of an example of invention types ofa conventional patent process. This figure represents the types ofinventions that are most often disclosed and include: fundamentalinventions, commercially necessary inventions, and commercial expansioninventions. A fundamental invention is one that is regarding afundamental concept of a technology that is being developed for a newproduct and/or new service. At times, a fundamental invention has beenreferred to as a “key” invention, a “pioneering” invention, or a“blocking” invention.

A commercially necessary invention is one that is regarding embodying afundamental concept into a minimally viable commercial product and/or toenable operation of the minimally viable commercial product. As usedherein, a “product” is physical or virtual thing that is bought, sold,leased, consumed, etc. by an end user and/or any entity in a productsupply chain. As also used herein, a “service” is the use of acommercial and/or proprietary product for the benefit of an end userand/or other entity in a service supply chain. Unless specificallystated otherwise, the discussion of processing inventions for patentingdiscussed herein is the same for inventions of services and as it is forinventions of products.

A commercial expansion invention is one that improves upon the minimallyviable commercial product by improving operating efficiency, reducingcost, improving reliability, improving features, adding new features,adding new functions, and/or other aspects that are intended to make aproduct more commercially attractive.

This figure also illustrates that a majority of inventions for a productwill be commercial expansion inventions. For example, 75% to 85% ofinventions are commercial expansion inventions; 10% to 15% of inventionsare commercially necessary patents; and 5% to 10% of inventions arefundamental inventions.

FIG. 1E is a schematic block diagram of an example of a conventionalpatent process with accompanying elements of the process. This diagramcombines the main components of invention disclosure & decide into onecomponent and adds the patent valuation as a new main component. Thus,for the diagram, the four main components of the conventional patentprocess include invention disclosure & decide, patent filing throughmaintenance, patent valuation, and patent use.

The invention disclosure & decide component includes the sub-componentsof invention identification, filing decision, and US & foreignpartitioning. The invention identification is primarily done byengineers, typically of different groups for larger companies. Theircatalyst for inventing is R&D and/or new product development. The issueswith engineer driven invention disclosure include too many inventionsdisclosures from some engineering groups, too few invention disclosuresfrom other engineering groups, most engineers disclose inventions basedon technical merit, not patentable value, limited overview of productsbeing developed, limited to no understanding of the level of innovationof new products being developed, too “now” focused (primarily patentingwhat's currently be developed and not enough on patenting what's tocome), and/or too “me” focused (primarily patenting what will go into aproduct, not enough focus on design-around options, and on how otherswould want to use the patented inventions).

The filing decision sub-component is executed by a patent committee andprimarily renders patenting filing decisions based on individual meritof an invention and annual budget constraints. The individual merit is a“bullet” focus based on the likelihood of being able to assert thepatent in litigation. The issues with conventional patent committeesinclude limited preparation work in reviewing inventions resulting intoo many good inventions not being patent protected, “bullet” focusresults in too many good inventions not being patent protected, too many“bullet-miss” (unusable patents or un-issuable patents) inventions getpursued, and/or no discernable focus on a patent protecting newtechnologies of new products. Default approach is allocating a certainnumber of new patent applications to groups developing a new product.

“Bullet” patents get a patent holder into litigation but it is thebreadth, depth, and strength of the relevant portions of a patentportfolio (“bulk” patents) that settle the litigation. It is estimatedthat 95% of patent lawsuits settle before trial. A settlement typicallyincludes a cross licensing agreement. Who pays who is based on who hasthe better relevant patent portfolio (the better “bulk” patents). Inthis instance, a first party has a better relevant patent portfolio ifthe second party's need for the first party's patent portfolio isgreater than the first party's need for the second party's patentportfolio.

The US & foreign sub-component is a patent portfolio management functionthat allocates the total budget among US patent matters and foreignpatent matters. A typical patent portfolio management system tracks theUS patent matters and the foreign patent matters. The allocation of thepatent budget was previously discussed.

The patent filing to maintenance component includes the sub-componentsof patent application preparation, patent application prosecution,patent issuance, subsequent patent application filings, and patentmaintenance. Issues with patent application preparation and prosecutioninclude too individual patent focused, lack of understanding of thetechnology, lack of understanding of the business use cases for theinvention, inadequate patent quality control measures, and/or inadequateunderstanding of patent laws, practices, rules, and/or guidelines.

The patent use component includes the sub-components of assertion,asset, market leverage, sale, and standards. The assertion sub-componentincludes bullet patents for litigation and bulk patents for licensing.The assert sub-component includes balance sheet value (market approach,cost approach, and/or income approach), collateral, and overall companyvalue. The market leverage sub-component includes market shareacquisition, market share protection, barrier to market entry, and/orsustainable market success.

The sale sub-component includes selling of unused patents, spin-off anew company, and/or creating a joint venture (JV). The standardssub-component includes standards essential and/or non-essential standardbut commercially necessary. The standards essential sub-component is forpatented inventions that are essential to implement a standard. Thenon-essential standard but commercially necessary sub-component is forpatent inventions that are no essential for implementing the standardbut are necessary to create a commercially viable product.

The conventional patent value component establishes value for some ofthe patent uses. For example, the conventional patent value processestablishes value for patents in litigation for the balance sheet value,for establishing value for collateral, and for patent sales. Theconventional patent value component does not include a mechanism tovalue market leverage. Even though market leverage is an important useof patents, the value of market leverage is not determined via theconventional patent process.

FIG. 1F is a schematic block diagram of an example of a conventionalpatent process with accompanying support services and data sources forthe process. In this diagram, the conventional patent process includesthe main components of invention disclosure, filing decision, patentapplication preparation and prosecution, portfolio management, andpatent use.

The data sources include a product & technology roadmap, an annualpatent portfolio budget, and an annual patent use budget. A product &technology roadmap typically includes, for products, a list anddescription of products in development and products to be developed. Fortechnology, the roadmap includes a list and description of technology tobe created, which is correlated to the products in development andproducts to be developed. In some roadmaps, a technology is listed thatis not currently earmarked for inclusion in a product, as such is itlisted as an R&D project. While product and technology roadmaps listproducts and technologies, they do not identify specific inventions tobe created, the timing of creating inventions, and the number ofinventions to be created as new products and/or new technologies aredeveloped.

The annual patent portfolio budget provides annual objects for thenumber of inventions to be disclosed, the number of disclosed inventionsto patent protect, the cost and quantity of on-going patent portfoliodevelopment matters, and patent portfolio maintenance. The annual patentuse budget is typically separate from the annual patent portfolio budgetand will vary greatly based on patent use programs.

The conventional patent process support services include inventionservices, preparation and prosecution services, portfolio maintenanceservices, and patent use services. The conventional invention servicesprovides support after inventions have been identified. For example,there are invention services that are directed towards individualinventors and very small companies to help them patent protect andmarket their invention. As another example, docketing systems used bylarger companies include a separate or integrated database for recordingand tracking inventions.

As used herein, a small company is referring to a company that files asmall number of patents per year regardless of the number of employeesthe company may have. A large company is referring to a company thatfile a significant number of patent per year regardless of the number ofemployees the company may have. In many situations, the number of patentfilings of a company corresponds to the number of engineers the companyhas.

The conventional patent preparation and prosecution services includedocketing services, prior art searching, freedom to operate searching,preparation of patent drawings, drafting of patent applications,drafting of office action response, automated drawing and specificationgeneration from a claim set, automated claim numbering and claimstructure review, and/or automated claim support in specificationanalysis.

The conventional portfolio maintenance services include docketing,annuity payments, portfolio culling, maintenance fee payment processing,patent landscape analysis, competitor patent analysis, and/or automatedvalue estimation of individual patents.

The conventional patent process is compartmentalized. The variouscomponents are owned and executed by different personnel with differentobjectives and different responsibilities. The is no one owner of theoverall patent process to coordinate the compartmentalized components.There is little to no feedback from the patent use component to theother component such the process is essentially an open loop. As aresult of the compartmentalized components, the individual inventionfocus, and the annual patent budge focus, the conventional process asinefficiencies that will be discussed in greater detail with referenceto FIG. 1 L.

FIG. 1G is a schematic block diagram of another example of aconventional patent process with accompanying patent data supportservices for the process. The various patent data services are one of adata aggregation service (light gray), a data analytics service (graygreen), or a structured data storage service (gray yellow).

The invention disclosure & decide component of the conventional patentprocess is supported by computer generated patent data analytic servicesregarding R&D trend data, patent trend data, and patent landscape data.The invention disclose & decide component is further supported by thestructured data storage of patent portfolio management.

The patent filing to maintenance component is supported by computergenerated patent data analytic services regarding filing and prosecutionstatistics, examiner data & statistics, law firm data & analysis, patentdrafting analysis, and prior art searching. The patent filing tomaintenance component is further supported by the structured datastorage of patent docketing.

The par patent valuation component is supported by computer generatedpatent data analytic services regarding citation analysis and worldwidefiling analysis. The per patent valuation component is further supportedby the manual processes of damage analysis and accounting analysis.

The patent use component is supported by computer generated patent dataanalytic services regarding patent landscape analysis and competitorpatent analysis. The patent use component is further supported by thestructured data storage of litigation document docketing. The patent usecomponent is further supported by computer generated patent dataaggregation services regarding patent litigation data, patent licensingdata, and patent sale data.

For data analytics, the reliability of the resulting data is only asgood as the inputted data and the manner of analysis. For theconventional patent process, the data analysis of examiners, of patentfilings, of patent prosecution, and of law firms is reliable since it isstatistical analysis of quantifiable data that can be reliably andrepeatedly retrieved.

The patent drafting analytics is reliable for patent structural issuessuch as claim number, proper use of antecedent basis, claim termsappearing the specification, and reference number consistency. Automatedpatent drafting software functions to generate initial figures and drafta specification from a claim set. Reviews of the most recent automatedpatent drafting software is that it provides a decent first draft of apatent application faster than the drafting patent attorney.

Such software, however, does not determine the substantive quality ofthe claims. The substantive quality of claims includes having cleardirect infringement targets, clarity of novelty aspects of theinvention, clarity of the invention, clarity of the problem being solvedby the invention, eliminate viable design around options, expansion ofthe inventive concept, and/or clearly identifiable benefits of theinvention.

The R&D trend analysis, the patent trend analysis, prior art searching,patent landscape analysis, and competitor patent analysis each have asignificant challenge in quantifying the patented technology to beanalyzed. Presently, the only universal patent-technology classificationmechanism is the classification codes used by Patent Offices. Forinstance, many Patent Offices use the IPC (international patentclassification) approach to classify incoming patent applications forexamination by the appropriate art group. The IPC classification systemincludes about 250,000 categories and sub-categories and was notdesigned for business level technology analysis. As such, it does notdirectly aligned with products and/or services and searching using theIPC yields varying quantifications of a technology and, thus, yieldsvarying data sets to analyze.

The per patent valuation data analytics of citation analysis andworldwide filing analysis have the ability to consistently obtainreliably data sets. The needed data is part of the patents. While datareliability is high, the manner of analysis is flawed. The citationanalysis relies on the premise that valuable patents are cited by otherpatents and, the more times a patent is cited, the more valuable it mustbe. The worldwide filing analysis is based on the premise that a patentholder files for international patent protection on its most importantinventions, thus those must be valuable inventions.

The citation premise is flawed because it relies on prior art cited bythe applicant and prior art cited by the examiner. Many applicants citetheir own prior art for a multitude of reasons including padding thenumber of times their patents are cited. With respect to examiners'prior art citings, an examiner has a limited amount of time to conduct aprior art search and, as such, an examiner's prior art search is notexhaustive. The premise is further flawed for newly emergingtechnologies, which won't be cited by others for a few years or more.

Despite the limitations of the various data services, it's estimatedthat the patent data service industry generates worldwide annual revenueof about a $21 billion. As machine learning and artificial intelligencesoftware continue to evolve, the patent data service industry isexpected to grow over the next several years.

FIG. 1H is a schematic block diagram of another example of aconventional patent process with accompanying support services for theprocess. In this diagram, the conventional patent process includes themain components of patent acquisition, patent ownership, and patentvaluation. Patent acquisition includes developing inventions andpatenting them; purchasing patents and/or patent applications; andlicensing patents.

Patent acquisition is supported by a plurality of patent acquisitionservice providers. For example, patent attorneys provide patentapplication and prosecution services for patenting a company'sinventions, such attorneys may be in-house or be affiliated with a lawfirm. Other examples include licensing attorneys, patent brokers andauctions, invention analytics, prior art searching, and freedom tooperate searching.

In this diagram, there are two types of patent holders: practicingentities (PE) and non-practicing entities (NPE). A practicing entitymakes a product and/or provides a service that embodies the patents theyown. A non-practicing entity does not make a product and/or provides aservice embodies the patents they own. Practicing entities range fromsmall companies to very large companies and non-practicing entitiesinclude patent trolls and defensive patent aggregation entities.

Patent holder services include patent docketing, maintenance and annuityfee paying services, in-house patent portfolio managers, patentportfolio management software, and in-house patent processes andprocedures, which include patent use strategies.

A patent portfolio has tangible value and intangible value. The tangiblevalue is realized through licensing, patent sales, and as assets.Tangible value is supported by tangible value services that includelitigation attorneys, licensing attorneys, in-house counsel, patentbrokers, patent valuation experts, expert witnesses, legal opinions,and/or litigation funds.

Intangible value corresponds to the market leverage that a patentportfolio provides. Market leverage includes market share protection,market share expansion, barriers to enter a market, and/or litigationdeterrent to practicing entities. The intangible value of a patentportfolio is not calculated, yet it may be as valuable or more valuablethan the patent portfolio's tangible value.

FIG. 11 is a schematic block diagram of an example of identifying anddisclosing inventions of a conventional patent process. In this example,an entity is developing a new product/service to address a targetedmarket opportunity. The new product/service includes three inventive newtech units A, B, and C. The product was designed by four groups ofengineers: one for the overall product, a second for new tech unit A, athird for new tech unit B, and a fourth for new tech unit C.

In this example, group discloses 1 invention; group 2 does not discloseany inventions, group 3 discloses 22 inventions, and group 4 discloses 5inventions for a total of 28 inventions. The patent committee decides topatent the inventions from group 1, 15 of the 22 inventions from group3, and 4 of the 5 inventions from group 4, totaling 20 inventions beingpatented.

The issue with this example is there is no way to (1) determine if 28inventions represents the total number of inventions for the new productor a small fraction of the innovation that went into producing the newproduct; (2) determine if 28 is the right number of inventions todisclose; (3) determine if the distribution of the 28 inventions fromthe 4 groups was appropriate; (4) determine if the 20 inventions electedfor patent protection were the right 20; and (5) determine if 20 of 28was the right percentage of inventions to patent.

The answers to these questions will not be answered unit the patentholder is involved in a patent dispute involving the new product, whichlikely will not occur for multiple years after the inventions werepatented. By then, it will almost certainly be too late to significantlychange the patent portfolio covering the new product.

In one possible scenario, the level of innovation of the new productincluded 200 new inventions, with 40 new inventions involving the newtech unit A. In this scenario, the other manufacturer of a like newproduct filed for patent protection on 120 inventions, including 30inventions for the new tech unit A. In a head to head patent dispute,the other manufacturer's 120 patents will force an unfavorable licensingagreement for the entity with the 20 patents.

FIG. 1J is a schematic block diagram of an example of a timeline of aconventional patent process. In this diagram, it takes about 2 to 4years for patents covering a technology to issue with respect to theirfiling dates. It's likely another 3 to 8 years before determining theeffectiveness of the patents covering the technology as illustrated inthe example of FIG. 11 .

This is a significant issue with the conventional patent process. Thereis no way to determine how well a technology is patent protected untilthe patents are needed for offensive and/or defensive purposes. Thisincludes the quantity of patents; the scope, breadth, and balance ofpatent coverage regarding the technology; and the quality of thepatents. By the time the patents are needed, it is often too late tocorrect for inadequate patent protection of a technology.

FIG. 1K is a schematic block diagram of an example of limitations of aconventional patent process used by large companies. The patentprocurement process is controlled by an annual patent plan that isbudget and individual patent driven; it uses a passive inventionidentification process driven by engineers; and it uses individualinvention filing decision metrics.

This yields a patent portfolio in which too many valuable inventions donot get disclosed by engineers and/or are not pursued because they donot fit well in the individual invention filing decision metrics. Thisalso yields a patent portfolio that is imbalanced having too few patentsregarding various innovative aspects of the technology and too manypatents for other innovative aspects of the technology. It also yields apatent portfolio that includes too many unnecessary patents (outside thescope of the technology, too many on one particular aspect, patentapplications that won't issue). It also yields a patent portfolio thisis too “me” focused and too “now” focused. All of this reduces the valueof the technology.

As discussed above, the deficiencies in a patent portfolio regarding atechnology are typically not discovered until the portfolio is needed.The convention patent process is reactive and employs a “take what youget” philosophy.

FIG. 1L is a schematic block diagram of another example of limitationsof a conventional patent process. As a result of the limitations of theconventional patent process, large companies typically over patent andsmall companies typically under patent. Large companies know fromexperience that many of the patents they obtain will have no value.Large companies also know that, if they file enough patents, some ofthem will have value and their value more than justifies the cost ofobtaining patents that have no value.

Small companies typically target patent protecting “key” or “blocking”patents via an ad hoc or check the box patent process. An ad hocapproach is to file patents if and when inventions are disclosed andthere is no formal process for when or how inventions are to bedisclosed. Many small companies adopt this approach because theirinvestors take a “check the box” approach to patents. The check the boxapproach verifies that a company has patents on the technology itsdeveloping and that is about it. There is little to no substantiveanalysis of the patents for quality and/or sufficiency of patentcoverage for the technology.

Nevertheless, the filing of patent applications has grown dramaticallyover the last twenty years reaching about 600,000 new patent applicationper year in the US. Of the 600,000 new patents 76% of them come from2,602 large companies (e.g., issuing 20 or more patents per year) andthe remaining 24% come from 44,800 small companies or individuals.

The filing rates have increased because the value of patentedtechnologies has also increased over the last twenty years. In 2019,worldwide R&D investments reached $2.4 trillion and about $240 billionwas invested in patent protecting the R&D. In the US in 2019, the grossdomestic product was about $21.38 trillion dollars of which, about $7.76trillion was attributable to intellectual property intensive industries.

There's no question that patents are big business, generatingsignificant revenues, even though the conventional patent process isinefficient. The inefficiency results in about $6 billion per year beingwasted in the US on patent application filings and prosecution that willnot result in issued patents.

The inefficiency also results in about $7 billion wasted annually in theUS on obtaining unnecessary patents. This includes patents that have novalue because of poor quality; because they are overkill of a technologyaspect; too few patents to have impact; and/or because they areregarding practically irrelevant aspects of a technology.

The inefficiency also results in lost opportunity of about $35 billionper year in the US. If a technology were patent protected with abalanced, appropriately sized patent portfolio of high quality, thisfinancial opportunity would be realized.

Throughout business, it is an objective to eliminate waste. Yet, when itcomes to the patent process, waste seems to be acceptable. A main reasonfor the waste is that the conventional patent process does not ask oranswer the question of how many patents are needed to appropriatelyprotect a technology. It does not ask or answer the question of whattypes of inventions should be protected, when should they be protected,and where should be they protected. Since the conventional patentprocess does not ask or answer these questions, it cannot calculate orforecast a patent return on investment for patent protecting atechnology.

FIG. 2 is a schematic block diagram of an example a company's valueproposition. In this example, a company's value is the combination ofthe value of its employees, the value of its business operations, thevalue of its brand, and the value of its technology. The latter threevalues propositions are driven by market demand & adoption of thecompany's products and/or services and on revenue generated from suchproducts and/or services. Market demand & adoption is driven bymarketing & brand recognition and, for technology companies, oninnovative and disruptive technology.

Value of the company's technology is also driven by how well it ispatent protected. This is a philosophical shift in valuing patents. Itis shifting from valuing patents on an individual basis, as is done inthe conventional patent process, to valuing a technology based on howwell its patent protected. Patent protecting a technology well includescreating a well balanced portfolio for the technology (equal andappropriate levels of patent protection for each technical challenge ofthe technology), a patent portfolio of appropriate breadth (covers usesand expansions of the technology), and a patent portfolio of highquality patents; and does so without waste (no unnecessary patents andno patent applications that won't issue).

When a technology is well patent protected, it provides the patentholder significant market leverage with respect to the technology.Market leverage adds to the value of the technology and this patentedtechnology valuation methodology captures the technology's full marketvalue by including market leverage.

Maximizing the value of technology through patent protection, helpsmaximize the overall value of a company. Increasing the value oftechnology helps drive the U.S. economy. As mentioned above, in the U.S.in 2019, the gross domestic product was about $21.38 trillion dollars ofwhich, about $7.76 trillion was attributable to intellectual propertyintensive industries (about 30% of which is directly attributable topatented technology).

Protecting technological development, driving growth of the economythrough technology advancements, and rewarding technology advancementswith limited time monopolies is rooted in the U.S. Constitution. Patentprotection of technology is regarding the invention or discovery of anynew and useful process, machine, manufacture, or composition of matter,or any new and useful improvement thereof.

There is no restriction on how a company may use patented technology toincrease its overall value. For example, companies embed the patentedtechnology in the products it sells. As another example, companies usepatented technology to increase production of the products it sells. Asa further example, companies use patented technology to improve trackingof production, quality control, and sales of the products. As yetanother example, companies use patented technology to improve otheraspects of its business operations and thus to increase the value ofbusiness operations. Regardless of how a technology is used by abusiness, if it helps the business increase its value, then thetechnology is helping drive the U.S. economy. Helping the U.S. economythrough technology advancement is at the heart of the Constitutionalright of patent protection.

To patent protect a technology well requires a paradigm shift andre-engineering of the patent process. It requires answering thequestions of (1) how many patents are needed to appropriately protect atechnology; and (2) what types of inventions should be protected, whenshould they be protected, and where should be they protected. To answerthese questions and more, a new computer architecture is disclosedherein, which provides an improved computer for technology.

As part of answer the questions, the improved computer for technologyexecutes, using machine learning and/or artificial intelligenceprograms, the method of FIGS. 3A through 3C. In FIG. 3A, the methodbegins at step 10 where the improved computer quantifies a technology byestablishing definitive boundaries. Via the improved computer,technology is quantified into market-tech units (MTUs), which arediscussed in greater detail in subsequent figures. In general, an MTU isa technology that has defined technical boundaries so it can be easilyand/or consistently identified, referenced, and/or searched.

The method continues at steps 12, 14, and 16. At step 12, the improvedcomputer calculates generational & phase development data for thequantified technology (i.e., a market-tech unit (MTU)). The generational& phase development data will be discussed in greater detail withreference to subsequent figures. In general, generational & phasedevelopment data is regarding S-curves of the quantified technologycovering per phase and per generation level of innovation, per phase andper generation breadth of innovation, per phase and per generationprofitability, and per phase and per generation technical evolution.

At step 14, the improved computer calculates a level of disruption ofthe quantified technology that spans the life of the quantifiedtechnology. The life of the quantified technology includes one or moregenerations of the quantified technology, where a new generation of thequantified technology corresponds to a 2X or more improvement of thequantified technology. The level of disruption will be described ingreater detail with reference to subsequent figures. In general, thelevel of disruption is a sliding scale from: incremental disruption,better mouse trap disruption, evolutionary disruption, and revolutionarydisruption.

In general, an incremental disruption quantified technology provides anenhancement to a predecessor technology and typically does not obsoleteproducts and exhibits modest perceptible performance improvements. Forexample, increasing a refresh rate of a video-graphics display is anincremental disruption. As another example, increasing the storagecapacity of a random access memory (RAM) chip is an incrementaldisruption.

In general, a better mouse trap disruption quantified technologyprovides a notable performance improvement of products that use thepredecessor technology. Products using the quantified technology forge anew section of a marketplace. While it takes market share form productsusing the predecessor technology, it does not generally obsolete suchproducts. For example, a shoe technology that improves the ground bodyconnection is a better mouse trap disruption.

In general, an evolutionary disruption quantified technology providesnew performances, features, functions, capabilities, etc. that were notobtainable from products that use predecessor technologies. Productsincorporating evolutionary technology typically obsolete products usingthe predecessor technology and expand the market. For example, LCDdisplays obsoleted CRT displays and expanded the display market.

In general, a revolutionary disruptive quantified technology opens upnew markets for products that have unprecedented performances, features,functions, capabilities, etc. For example, the internet opened upe-commerce markets and a plethora of other on-line products.

At step 16, the improved computer routinely (e.g., periodically,pseudo-randomly, upon command, etc.) gathers marketing, sales, business,technology, and patent (MSBTP) documents relating to a quantifiedtechnology. The improved computer extracts data from the MSBTP documentsto help define, expand, and categorize the quantified technology in aservice and/or product supply chain.

Steps 12, 14, and 16 lead to steps 18, 20, and 22. At step 18, theimproved computer calculates a level of innovation for the life of thequantified technology based on the generational & phase data, the levelof disruption, and the MSBTP data. The level of innovation correspondsto the number of technical challenges that need to be resolved to makecommercially viable products over the life of the quantified technology,which may span multiple generations. In general, a technical challengecorresponds to a technical aspect of a unique value proposition (UVP) ofquantified technology, a technical aspect of a marketable feature ofproducts embodying (or likely to embody) the quantified technology,and/or other technical aspect of the quantified technology.

At step 20, the improved computer calculates the current (and past)market impact of the quantified technology based on the generational &phase data, the level of disruption, and the MSBTP data. In general, themarket impact of a quantified technology is a financial measure of itsinfluence on transactions of products embodying the quantifiedtechnology and uses thereof. As an example, a touch screen controllerchip retails for $1 per chip and 1 billion chips are sold annually.Assume that the quantified technology is embodied in all of the touchscreen controller chips sold. As such, the annual total revenue for thechips is $1 billion. Assume that 25% of the value of the chip isattributable to the quantified technology, then the market impact of thequantified technology is $250 million (25% of $1 billion).

As another example, assume that the touch screen controller chip withthe quantified technology enables new touch related features, services,functions, etc. of a cell phone. Assume that the annual revenue for cellphone sales is $500 billion. Further assume, that the new touch relatedfeatures, services, functions, etc. account for 0.5% of the value of acell phone. Based on these assumptions the quantified technology has anadditional value of $2.5 billion (0.5% of $500 billion).

At step 22, the improved computer calculates the future impact of thequantified technology based on the generational & phase data, the levelof disruption, the MSBTP data, and the current market impact of thequantified technology. Continuing with the examples of step 20, thefuture forecast for the touch screen controller chip is that it willevolve to include further features, functions, performance enhancements,etc. The future forecast is that the sale of touch screen controllerchips will have a CAGR (compounded annual growth rate) of 8% for thenext 5 years and the price per chip will have a CAGR of 1% for the nextfive years. The future forecast further includes that the sales of cellphones will have a CAGR of 4% for the next five years and the price percell phone remain constant. The future forecast further includes thatthe touch screen controller will be incorporated in tablets, laptops,and smart watches.

From step 18, the method continues at steps 28 and 34. At step 28, theimproved computer calculates a current level of inventions for thequantified technology. To do this, the improved computer determines atotal number of inventions to be invented over the life of thequantified technology (which may include multiple generations). Based onthe generational and phase data of step 18, the improved computerdetermines how much of the life of the quantified technology has passed.From the total number of inventions and how much of the life has passed,the improved computer determines the total number of inventions thatshould have been invented to date.

At step 34, the improved computer calculates a future level ofinventions. To do this, the improved computer uses the total number ofinventions and how much of the life has passed to determine the totalnumber of inventions that should be invented in the future to the end oflife of the quantified technology.

From step 28, the method continues at step 30, where the improvedcomputer calculates a current patent position. To do this, the improvedcomputer determines an actual number of inventions regarding thequantified technology have some form of patent protection (e.g.,disclosed in a pending provisional patent application, disclosed in apending patent application, claimed in an issued patent). The improvedcomputer also determines an ideal number of inventions of the quantifiedtechnology that should have some form of patent protection. The idealnumber of inventions is based on the total number of inventions thatwarrant patent protection (e.g., have value in a patent fence protectingthe quantified technology; a patent fence is discussed in detail withreference to subsequent figures). The ideal number of inventions willtypically be in the range of 60% to 95% of the total number ofinventions.

The improved computer then compares the actual number of inventionsprotected with respect to the ideal number of inventions that shouldhave been patent protected to date. The comparison establishes thecurrent patent position of the industry as a whole and/or for individualpatent holders. The patent position ranges from weak to superior on asliding scale. A superior patent position corresponds to a very highprobability of a favorable outcoming in a patent dispute involving thequantified technology. A weak patent position corresponds to a very highprobability of an unfavorable outcoming in a patent dispute involvingthe quantified technology. A superior patent position includes actualinventions patent protected in the range of 35% to 80% of the idealnumber of inventions.

From steps 20 and 30, the method continues at steps 24 and 36. At step24, the improved computer calculates the current value of the quantifiedtechnology. The current value is calculation as a function of how wellthe quantified technology is patent protected (e.g., a calculatednumerical representation of its current patent position), the currentmarket impact as determined in step 20, and a market-technology “k”factor. The value of quantified technology as MTUs (market-tech units)will be described in greater detail with reference to subsequentfigures.

From steps 22, 32, and 34, the method continues at step 26. At step 32,the improved computer determines a desired future patent position. Thisis typically based on an input from a user of the improved computer. Atstep 26, the improved computer calculates the future value of thequantified technology based on the future market impact of step 22, thedesired patent position of step 32, and the calculated level ofinventions from step 34. The future value is calculation as a functionof how well the quantified technology is planned to be patent protected(e.g., a calculated numerical representation of its future patentposition), the future market impact as determined in step 22, and themarket-technology “k” factor.

The method continues at step 36, where the improved computer generatesan architectural plan, as a tangible digital output, for the quantifiedtechnology based on the inputs received from steps 24, 26, 30, 32, and34. The architectural plan includes a targeted number of inventions topatent protect each year, where to seek patent protection, the projectedannual cost of patent protection and growing a patent portfolio, theprojected growth of the patent portfolio, and the projected value of thequantified technology. The targeted inventions include targetedinvention types and targeted quantities for each technical challenge ofthe quantified technology. The generation of an architectural patentprotection plan will be discussed in greater detail with reference tosubsequent figures.

The method continues at step 38, where the improved computer tracksexecution of the architectural patent protection plan via trackingmachine learning and/or artificial intelligence programs and privatepatent portfolio development databases.

The method continues at step 40, where the improved computer executesmachine learning and/or artificial intelligence programs regardingpatent application drafting and/or patent application prosecution inaccordance with the architectural patent protection plan. The methodcontinues at step 42, where the improved computer executes machinelearning and/or artificial intelligence programs to identify patent useopportunities in accordance with the architectural patent protectionplan.

FIG. 3B is a logic diagram of a method that is in furtherance of themethod of FIG. 3A and, in particular, with respect to steps 18, 28, and34 of FIG. 3A. In the present figure, step 18, which is regarding thecalculation of the level of innovation, includes steps 44 and 46. Atstep 44, the improved computer calculates a total number of inventionsand invention types for the life of the quantified technology. Step 18then continues at step 46, where the improved computer calculates anideal number of inventions and invention types to protect over the lifeof the quantified technology. The total number of inventions and theideal number of inventions corresponds to the level of innovation.

Step 28, which is regarding the calculation of the current inventionlevel, includes the steps 48 and 50. At step 48, the improved computercalculates a current a total number of inventions and a current idealnumber of inventions that should have been invented to date. Step 28continues at step 50, where the improved computer calculates the currentinvention patent protection level for the quantified technology based onthe total and ideal numbers and an actual number of inventions havingsome form of patent protection to date.

Step 34, which is regarding the calculation of the future level ofinventing, includes the steps 52 and 54. At step 52, the improvedcomputer calculates a future total number of inventions and a futureideal number of inventions that should be invented before the end oflife of the quantified technology. Step 34 continues at step 54, wherethe improved computer calculates the future invention patent protectionlevel for the quantified technology based on the future total and idealnumbers and a desired future patent position.

FIG. 3C is a logic diagram of a method that is in furtherance of themethod of FIG. 3A and, in particular, with respect to steps 24 and 26 ofFIG. 3A. In the present figure, step 24 includes steps 54, 56, 58, and60 and step 26 includes steps 54, 62, 64, and 66. At step 54, theimproved computer calculates the market-patent “k” factor, which is asliding scale of a measure of patent need and technologycompetitiveness. The market-patent “k” factor will be described ingreater detail with reference to subsequent figures.

At step 56 of step 24, the improved computer calculates quality ofcurrent patent protection (e.g., the quality of patent applicationpreparation and/or patent application prosecution). The method continuesat step 58, where the improved computer calculates a to-date how well isthe quantified technology patent protected. The method continues at step60, where the improved computer calculates the current value of thequantified technology based on the “how well patent protected” value,the current market impact, and the “k” factor.

At step 62 of step 26, the improved computer calculates quality offuture patent protection (e.g., the likely quality of to be filed patentapplications and/or to be prosecuted patent applications). The methodcontinues at step 64, where the improved computer calculates a futurehow well the quantified technology will be patent protected. The methodcontinues at step 66, where the improved computer calculates the futurevalue (on a year by year basis) of the quantified technology based onthe future “how well patent protected” value, the future market impact,and the “k” factor.

FIG. 4A is a schematic block diagram of an embodiment of an improvedcomputer 70 for technology that includes an MSBTP (marketing, sales,business, technical, and patent) data gathering section 72, systemdatabases 74, a processing section 76, a subscription based userinterface section 78, and a subscription pricing section 80, which aresupported by one or more computing entities. In general, the MSBTP datagathering section 72 executes machine learning and/or artificialintelligence programs to routinely (e.g., periodically, pseudo randomly,upon request, etc.) ingest a large number of documents and dissect eachdocument for relevant information regarding existing market-tech units(MTUs) and potentially new MTUs, where an MTU is a piece of quantifiedtechnology.

Relevant documents come in a variety of forms, are of a variety oftypes, and contain information regarding a variety of technology relatedtopics. The form of a document is either a digital form or a physicalform (e.g., printed on a piece of paper, in a printed newspaper, in aprinted magazine, etc.). For documents in physical form to be ingestedby the MSBTP data gathering section, the document is scanned to producea digital version of it.

A digital form document, it is formatted in accordance with one or moredocument formats. For example, a document is a PDF (portable documentformat) document, another document is an HTML (hypertext markuplanguage) document, another document is a word processing document,another document is a spreadsheet, another document is an image of oneor more image formats (JPEG, PNG, GIF, SVG, MP4, etc.), and/or any othermanner of digitizing information.

The document type is one or more of, but not limited to, a scholarlypaper, an article, an essay, a study, a report (market, financial,business, technical, etc. that is regarding the past, present, and/orfuture), a manuscript, a deed, a certificate, a file, an experiment, asummary, a compilation, a data sheet, marketing material, salesmaterial, an annual report, a patent, a patent application, a businessplan, and a record.

The relevant content of document is information regarding an MTU'stechnical boundaries, its MTU inclusion hierarchy, its MTU compositionhierarchy, functionality, its market impact, science categories, itsinventions and patent protection thereof, and/or manufacturing. Each ofthese content categories will be discussed in greater detail withreference to subsequent figures. As a non-exhaustive list of examples,the document content includes information regarding technology,businesses that leverage (use, buy, sell, trade, lease, etc.)technology, financial data regarding technology, past and current marketdata regarding technology, transactions (buy, sell, license, litigate,etc.) regarding technology, development of new technology, requirementsof a technology, standardizations of a technology, legal regulations ofa technology, revenue forecasts regarding products/services embodyingtechnology, and forecasts of future technology.

For documents ingested by the MSBTP data gathering section 72, itgenerates data for a MSBT (marketing, sales, business, technology)record to be created in an MSBT database; it generates data for anannotated patent record to be created in an annotated patent database;and it generates data for a patent term record to be crated in a patentterm database if the ingested patent contains a new patent term (i.e.,not already in the patent term database).

As documents are ingested, the MSBTP data gathering section 72 tags themwith an MTU classification, which includes the classification of theMTU(s) name if the document is clearly associated with the MTU(s), theclassification of “undecided, potential new MTU” if the document is notclearly associated with an existing MTU but is likely associated with apotentially new MTU, or a classification of “undecided” if the documentis not clearly associated with an existing MTU or a potentially new MTU.

For a document that is tagged with an MTU name, relevant informationregarding the document is added to the MTU record regarding the MTU inan MTU database. The MSBTP data gathering section 72 routinely (e.g.,periodically (minutes, hours, days), pseudo-randomly, upon command)reviews the documents that have been classified “undecided, potentialnew MTU” to determine if there is sufficient data to establish a newMTU, to establish that there is not a new MTU, and/or to reclassify adocument. The MSBTP data gathering section 72 also routinely reviewsdocuments with the classification of “undecided” to determine if theyshould be reclassified or ultimately deleted.

When there is sufficient data to establish a new MTU, MSBTP datagathering section 72 generates data to create a new MTU record in theMTU database. The data includes the documents used to establish theexistence of a new MTU.

From the records in the MSBT database, the annotated patent database,and/or the patent term database, the MSBTP data gathering section 72generates market impact data for an MTU. The market impact data includesexisting market impact data and future forecasted market impact data.

The processing section 76, as will be discussed in greater detail withreference to subsequent Figures, includes machine learning and/orartificial intelligence programs that function based on an MTU operatingsystem and in accordance with a re-engineered patent process. Theprocessing section 76 produces a plurality of digital reports regardingone or more MTUs, which include, for example, an existing TMPVI(technology, market impact, patent protection, innovation, and/or value)report 82; a future TMPVI report 84, a TMPVI development report 86(which includes an architectural plan to patent protect an MTU); adrafted patent application and/or claim set 88; a patent prosecutionresponse 90; a patent use opportunities report 92, and/or a constructivenotice report 94.

Per the re-engineered patent process, an architectural patent protectionplan is created by the processing section 76 for an MTU as early in thedevelopment of the MTU as practically possible. Using machine learningand/or artificial intelligence programs, which will be described indetail with subsequent figures, the processing section 76 calculates thetotal number of inventions that are likely to be invented over the lifeof the MTU based on, at least in part, technical challenges of the MTU;calculates invention types breakdown of the total number of inventions;calculates how many of the total number of inventions should be patentprotected based on a desired patent position balanced with a desiredpatent spend and desired patent ROI (return on investment); anddetermines, when, where, and how to patent protect selected inventions.

In this manner, a patent portfolio for an MTU is built in accordancewith a detailed architectural plan, which can be adjusted as thetechnology and/or market of the MTU evolve. As such, every inventionthat is patent protected is done so with a purpose in accordance withthe plan, there is virtually no waste due to unnecessary patents, theresulting patent portfolio is balanced, of the desired scope and breadthto maximize the value of the MTU. When the patent application draftingand prosecution tools of the improved computer are used, waste due tofiling patent applications that will not issue or issue with fatal flawsis eliminated.

As an analogy, the architectural plan to patent protect an MTU(market-tech unit, which a quantifiable piece of technology) is similarto the architectural plan for a building. The architectural plan for abuilding defines the size of the building, the shape of the building,the types of rooms in the building and quantity for each, the plumbing,the electrical, the HVAC, and so on. Every detail of the building ismapped out before building materials are purchased and constructioncommences.

The architectural plan to patent protect an MTU defines the size of thepatent protection (number of inventions to protect), the type ofinventions to protect and when & how to protect them, the technologychallenges to be addressed, which leads to problems to be solved,inventive concepts for solving the problems, and particular solutions.In essence, every detail for building a patent portfolio to protect anMTU is mapped out as early in the development of the MTU as possible.This insures, like a building, that only necessary building materialsare being acquired so that waste is minimized, and the desired structureis created (building or patent portfolio).

In contrast, the conventional patent process, which does not determinethe number of inventions to patent protect for a technology over itslife and does not quantify a technology in definitive terms that clearlydefines technical boundaries, is like collecting building materials overseveral years for a variety of suppliers of which, some regularlyprovide certain building materials and others rarely provide other typesof building materials. Then, years later collecting an imbalance ofbuilding materials, determining what can be built from the collectedbuilding materials.

If such an approach were taken with constructing a building, acontractor would collect too many building materials from some sources(e.g., plumbing supplies, roofing materials, paint, floor covering) andreceiving too few building materials from other sources (e.g., framingmaterial, electrical, drywall) over a multi-year period. After years ofgathering various building materials in this manner, the contractor nowdecides what can be built with the collected building materials.Clearly, what can be built would have some functioning building elementsbut would not resemble the building that was constructed from a detailedarchitectural plan.

The improved computer 70 includes a new computer architecture that usesa new MTU operating system and system level machine learning and/orartificial intelligence programs to balance data analytics performed byuser machine learning and/or artificial intelligence programs on theimproved computer. The balancing of data analytics is to keep reports,summaries, and/or plans at the digestible pieces of meaningfulinformation level and avoid swinging too far into the details orswinging too far into the general. With too far into the detail, theimportant take-aways of the data analysis are lost in the detail. Withtoo far into the general, any important take-aways are lost ingenerality.

Within the improved computer 70, the user machine learning and/orartificial intelligence programs are software tools with the samepurpose as any tool. In general, a tool (physical and/or virtual)provides a useful function for its user by improving something, makingsomething more efficient, making something more reliable, makingsomething faster, etc., where the something is an aspect of the user'slife (e.g., making a business more financially sound, providing betterproduction (output &/or efficiency), providing more efficient businessfunctions, making a higher quality product, and so on). From a businessstandpoint, any tool that aids in increasing the value of the company isa valuable tool, regardless of its particular function.

FIG. 4B is a schematic block diagram of another embodiment of animproved computer 70 for technology. The improved computer 70, which isimplemented using one or more computing entities, includes a hardwaresection 102 and a software programs 100. The hardware section 102includes a processing core, a plurality of co-processors (e.g., aco-processor is a processing core of a computing entity, is astand-alone processing unit, and/or is a section of a processing unit),private databases, system databases, main memory, secondary memory,network communication access devices (e.g., WAN (wide area network), LAN(local area network, wired and/or wireless), the Internet, etc.), userinterfaces, and power management.

The software programs 100 include a computing entity operating system104, an MTU operating system 106, MTU machine learning and/or artificialintelligence system applications, MTU machine learning and/or artificialintelligence user applications, MTU system application programminginterfaces (APIs), and MTU user application APIs. The computing entityoperating system 104 includes hardware interfaces (HWI) for the varioushardware components of the hardware section 102. The MTU operatingsystem (OS) 106 includes OS programs regarding MTU private database (DB)management, MTU system DB management, MTU content management, MTUcorrelation, user interface management, security management, errordetection and correction management, and MTU process management.

The MTU operating system 106 interacts with the computing entityoperating system 104 via an operating system (OS) to operating system(OS) interface. The OS to OS interface primarily functions as atranslator between the OS programs of the MTU operating system and theOS programs of the computing entity operating system 104, which includeprocess management, command interpreter system, input/output devicemanagement, main memory management, file management, second storagemanagement, error detection and management, and security management.

The MTU operating system 106 controls the operation of the MTU systemapplications. The MTU system applications include machine learningand/or artificial intelligence programs for identifying data, gatheringdata, extracting relevant information from the data, MTU (market-techunit) classifying the data, creating MTUs, creating and updating MTUrecords, creating and updating MSBT (marketing, sales, business,technology) records, creating and updating patent data records, creatingand updating market impact records, storing MTU records, storing MSBTrecords, storing patent data records, and storing market impactrecords).

The MTU operating system 106 also controls the operation of the MTU userapplications. The MTU user applications include machine learning and/orartificial intelligence programs regarding MTU generation and phasecalculations and/or report generation, MTU existing patent datacalculations and/or report generation, MTU existing marketing impactcalculations and/or report generation, MTU existing patent protectioncalculations and/or report generation, MTU previous & current valuationcalculations and/or report generation, MTU future forecasted patent datacalculations and/or report generation, MTU future forecasted marketingimpact calculations and/or report generation, MTU future forecastedpatent protection calculations and/or report generation, MTU futureforecasted valuation calculations and/or report generation, MTUtechnology expansion calculations and/or report generation, MTU marketopportunity calculations and/or report generation, MTU market expansioncalculations and/or report generation, MTU patent portfolio growth &expense calculations and/or report generation, MTU patent protectionplan calculations and/or report generation, MTU future valuecalculations and/or report generation, MTU invention identification andclaim drafting calculations and/or report generation, MTU patentapplication drafting calculations and/or report generation, MTU patentprosecution response calculations and/or report generation, MTU patentquality calculations and/or report generation, MTU patent plan execution& tracking calculations and/or report generation, MTU constructivenotice calculations and/or report generation, MTU patent saleopportunity calculations and/or report generation, MTU patent purchaseopportunity calculations and/or report generation, MTU patent licensingopportunity calculations and/or report generation, MTU patent standardsopportunity calculations and/or report generation, and MTU patent basedspin-off or joint venture (JV) opportunity calculations and/or reportgeneration.

The operation of the improved computer 70, the hardware section 102 andthe software programs 100 will be described in greater detail withreference to subsequent figures. In an embodiment, the improved computerperforms the method of FIGS. 3A through 3C.

FIG. 4C is a diagram of an embodiment of operating system functions ofan improved computer for technology in tabular form. The MTU operatingsystem functions set rules the MTU system applications and for the MTUuser applications and include MTU process management, MTU contentmanagement, MTU correlation, MTU system DB management, MTU privatedatabase (DB) management, user interface management, securitymanagement, and error detection and correction management.

The MTU process management OS function manages processes (e.g., aprocess is a running program or a sub-routine thereof) of the MTUoperating system, of the MTU system applications, and/or MTU userapplications based on general rule concepts. The rules includeprioritizing MTU operating system processes over MTU system applicationprocesses, which have priority over MTU user application processes. Therules also include only one write to a field of data record at a timeand no limits on concurrent reading from data records.

As at least part of managing processes, the MTU process management OSfunction manages access to the hardware section of the improvedcomputer, avoids deadlock of processes, prioritizes processes per therules, and avoids starvation of processes. Controlling access to thehardware section includes communicating with the computing entityoperating system to allow processes access to the processing core, theMTU co-processors, a private database, a system database, main memory,secondary memory, a network connection, and/or a user interface.Controlling access involves creating, loading, executing, suspending,resuming, and/or termination processes access to the hardware. Itfurther involves switching between multiple processing in main memory,providing communication between the processes as needed, and/or managingconcurrent accesses to a particular hardware component by multipleprocesses.

The MTU content management OS function manages and regulates whatconstitutes an MTU and manages and regulates the evolution of MTUs inaccordance with its general rules. The general rules prescribe a minimumrequirement for technical boundaries of a technology for it to bequantified as an MTU. The minimum requirements include one or moremarketable features and/or one or more unique value propositions (UVP),one or more technical challenges relating to the marketable feature(s)and/or the UVP(s), and new and/or existing innovation based on thetechnical challenge(s).

The MTU content management OS function controls the identification ofnew MTUs, of creating data for new MTU data records, for creating datafor data populating existing MTU records, and for editing data ofexisting MTU records. The MTU content management OS function furthermanages the splitting of an MTU into two or more MTUs, manages themerger of two more MTUs into one MTU, and manages the obsoleting ofMTUs.

The MTU correlation OS function manages correlation of patent data andMSBT (marketing, sales, business, technical) data with MTUs (market-techunits, which represent quantified technology) based on general rules.The general rules include that MTU correlation includes MTU inclusiondata (e.g., what an MTU is included in at least the next higher MTUtier), includes MTU composition data (e.g., what, of at least the nextlower MTU tier, is included in the present MTU), and that MTU inclusiondata in not required for fundamental MTUs.

The MTU correlation OS function manages correlation of newly ingestpatent data and MSBT data with MTUs; it manages updating correlation ofexisting patent data and/or MSBT data as MTUs evolve; and it managesupdating correlation of existing patent data and/or MSBT data as newMTUs are created.

The MTU system DB management OS function manages access to systemdatabases based on general rules. The general rules include no externalaccess to the system databases, access can only be through an MTU userapplication or an MTU system application, writing (e.g., create newrecords, edit records, delete records, etc.) can only be done by an MTUsystem application, and MTU user application only have read access tosystem databased.

Based on the rules, the MTU system DB management OS function managesreads and writes to the system databases; manages creating new systemdatabase records, manages deletion of system database records; andmanages MTU addressing of system data.

The MTU private database (DB) management OS function manages access toprivate databases based on general rules. A private databases storesdata for a user account regarding the planning and execution building apatent portfolio for an MTU. The general rules include that a privatedatabased can only be accessed via selected MTU user applications byauthorized users as approved through the user interface management OSfunction. The general rules further include field level read and/orwrite access for authorized users.

Based on the rules, the MTU private DB management OS function managescreating new private databases, manages reads and writes to privatedatabases; manages creating new private database records, managesdeletion of private database records; and manages MTU addressing ofprivate data.

The user interface management OS function control user access to theimproved computer for technology.

Basically, unless a user, via its computing device, has properauthorization to access an MTU user application regarding one or moreselected MTUs, the user is not permitted to access the improvedcomputer. For example, the user may be a valid user but is seeking toaccess MTUs it is not authorized to access (e.g., has not subscribed toaccess such MTUs).

The MTU security management OS function rides on top of the security OSfunction of the computing entity operating system. MTU security monitorsthe ingesting of data from vetting data sources and the vetting ofreceived documents prior to ingesting the document into the improvedcomputer. The MTU security also monitors access to the MTU systemapplication and ensures that it only done by authorized systemadministrators.

The MTU error detection and correction management OS function rides ontop of the error detection and correction OS function of the computingentity operating system. The MTU error detection and correctionmanagement OS function detects processing errors of MTU OS functions, ofMTU system applications, and/or of MTU user applications; processesdebugging of MTU OS functions, of MTU system applications, and/or of MTUuser applications; processes diagnostics of MTU OS functions, of MTUsystem applications, and/or of MTU user applications; and detectspotential deadlocks and/or infinite loops of MTU OS functions, of MTUsystem applications, and/or of MTU user applications.

FIGS. 5A through 5E are schematic block diagram of embodiments ofcomputing entities that form at least part of an improved computer fortechnology. FIG. 5A is schematic block diagram of an embodiment of acomputing entity 110 that includes a computing device 120 (e.g., one ormore of the embodiments of FIGS. 6A-6G). A computing device may functionas a user computing device, a server, a system computing device, a datastorage device, a data security device, a networking device, a useraccess device, a cell phone, a tablet, a laptop, a printer, a gameconsole, a satellite control box, a cable box, etc.

FIG. 3B is schematic block diagram of an embodiment of a computingentity 110 that includes two or more computing devices 120 (e.g., two ormore from any combination of the embodiments of FIGS. 6A-6G). Thecomputing devices 120 perform the functions of a computing entity in apeer processing manner (e.g., coordinate together to perform thefunctions), in a master-slave manner (e.g., one computing devicecoordinates and the other support it), and/or in another manner.

FIG. 3C is schematic block diagram of an embodiment of a computingentity 110 that includes a network of computing devices 120 (e.g., twoor more from any combination of the embodiments of FIGS. 6A-6G). Thecomputing devices are coupled together via one or more networkconnections (e.g., WAN, LAN, cellular data, WLAN, etc.) and preform thefunctions of the computing entity.

FIG. 3D is schematic block diagram of an embodiment of a computingentity 110 that includes a primary computing device (e.g., any one ofthe computing devices of FIGS. 6A-6G), an interface device (e.g., anetwork connection), and a network of computing devices 120 (e.g., oneor more from any combination of the embodiments of FIGS. 6A-6G). Theprimary computing device utilizes the other computing devices asco-processors to execute one or more the functions of the computingentity, as storage for data, for other data processing functions, and/orstorage purposes.

FIG. 3E is schematic block diagram of an embodiment of a computingentity 110 that includes a primary computing device (e.g., any one ofthe computing devices of FIGS. 6A-6G), an interface device (e.g., anetwork connection) 122, and a network of computing resources 124 (e.g.,two or more resources from any combination of the embodiments of FIGS.6A-6G). The primary computing device utilizes the computing resources asco-processors to execute one or more the functions of the computingentity, as storage for data, for other data processing functions, and/orstorage purposes.

FIGS. 6A through 6G are schematic block diagram of embodiments ofcomputing devices that form at least a portion of a computing entity.FIG. 6A is a schematic block diagram of an embodiment of a computingdevice 120 that includes a plurality of computing resources. Thecomputing resources, which form a computing core, include one or morecore control modules 130, one or more processing modules 132, one ormore main memories 136, a read only memory (ROM) 134 for a boot upsequence, cache memory 138, one or more video graphics processingmodules 140, one or more displays 142 (optional), an Input-Output (I/O)peripheral control module 144, an I/O interface module 146 (which couldbe omitted if direct connect 10 is implemented), one or more inputinterface modules 148, one or more output interface modules 150, one ormore network interface modules 158, and one or more memory interfacemodules 156.

A processing module 132 is described in greater detail at the end of thedetailed description section and, in an alternative embodiment, has adirection connection to the main memory 136. In an alternate embodiment,the core control module 130 and the I/O and/or peripheral control module144 are one module, such as a chipset, a quick path interconnect (QPI),and/or an ultra-path interconnect (UPI).

The processing module 132, the core module 130, and/or the videographics processing module 140 form a processing core for the improvedcomputer. Additional combinations of processing modules 132, coremodules 130, and/or video graphics processing modules 140 formco-processors for the improved computer for technology. Computingresources 124 of FIG. 5E include one more of the components shown inthis Figure and/or in or more of FIGS. 6B through 6G.

Each of the main memories 136 includes one or more Random Access Memory(RAM) integrated circuits, or chips. In general, the main memory 136stores data and operational instructions most relevant for theprocessing module 132. For example, the core control module 130coordinates the transfer of data and/or operational instructions betweenthe main memory 136 and the secondary memory device(s) 160. The dataand/or operational instructions retrieve from secondary memory 160 arethe data and/or operational instructions requested by the processingmodule or will most likely be needed by the processing module. When theprocessing module is done with the data and/or operational instructionsin main memory, the core control module 130 coordinates sending updateddata to the secondary memory 160 for storage.

The secondary memory 160 includes one or more hard drives, one or moresolid state memory chips, and/or one or more other large capacitystorage devices that, in comparison to cache memory and main memorydevices, is/are relatively inexpensive with respect to cost per amountof data stored. The secondary memory 160 is coupled to the core controlmodule 130 via the I/O and/or peripheral control module 144 and via oneor more memory interface modules 156. In an embodiment, the I/O and/orperipheral control module 144 includes one or more Peripheral ComponentInterface (PCI) buses to which peripheral components connect to the corecontrol module 130. A memory interface module 156 includes a softwaredriver and a hardware connector for coupling a memory device to the I/Oand/or peripheral control module 144. For example, a memory interface156 is in accordance with a Serial Advanced Technology Attachment (SATA)port.

The core control module 130 coordinates data communications between theprocessing module(s) 132 and network(s) via the I/O and/or peripheralcontrol module 144, the network interface module(s) 158, and one or morenetwork cards 162. A network card 160 includes a wireless communicationunit or a wired communication unit. A wireless communication unitincludes a wireless local area network (WLAN) communication device, acellular communication device, a Bluetooth device, and/or a ZigBeecommunication device. A wired communication unit includes a Gigabit LANconnection, a Firewire connection, and/or a proprietary computer wiredconnection. A network interface module 158 includes a software driverand a hardware connector for coupling the network card to the I/O and/orperipheral control module 144. For example, the network interface module158 is in accordance with one or more versions of IEEE 802.11, cellulartelephone protocols, 10/100/1000 Gigabit LAN protocols, etc.

The core control module 130 coordinates data communications between theprocessing module(s) 132 and input device(s) 152 via the input interfacemodule(s) 148, the I/O interface 146, and the I/O and/or peripheralcontrol module 144. An input device 152 includes a keypad, a keyboard,control switches, a touchpad, a microphone, a camera, etc. An inputinterface module 148 includes a software driver and a hardware connectorfor coupling an input device to the I/O and/or peripheral control module144. In an embodiment, an input interface module 148 is in accordancewith one or more Universal Serial Bus (USB) protocols.

The core control module 130 coordinates data communications between theprocessing module(s) 132 and output device(s) 154 via the outputinterface module(s) 150 and the I/O and/or peripheral control module144. An output device 154 includes a speaker, auxiliary memory,headphones, etc. An output interface module 150 includes a softwaredriver and a hardware connector for coupling an output device to the I/Oand/or peripheral control module 144. In an embodiment, an outputinterface module 150 is in accordance with one or more audio codecprotocols.

The processing module 132 communicates directly with a video graphicsprocessing module 140 to display data on the display 142. The display142 includes an LED (light emitting diode) display, an LCD (liquidcrystal display), and/or other type of display technology. The displayhas a resolution, an aspect ratio, and other features that affect thequality of the display. The video graphics processing module 140receives data from the processing module 132, processes the data toproduce rendered data in accordance with the characteristics of thedisplay, and provides the rendered data to the display 142.

FIG. 6B is a schematic block diagram of an embodiment of a computingdevice 120 that includes a plurality of computing resources similar tothe computing resources of FIG. 6A with the addition of one or morecloud memory interface modules 164, one or more cloud processinginterface modules 166, cloud memory 168, and one or more cloudprocessing modules 170. The cloud memory 168 includes one or more tiersof memory (e.g., ROM, volatile (RAM, main, etc.), non-volatile (harddrive, solid-state, etc.) and/or backup (hard drive, tape, etc.)) thatis remoted from the core control module and is accessed via a network(WAN and/or LAN). The cloud processing module 170 is similar toprocessing module 132 but is remoted from the core control module and isaccessed via a network.

FIG. 6C is a schematic block diagram of an embodiment of a computingdevice 120 that includes a plurality of computing resources similar tothe computing resources of FIG. 6B with a change in how the cloud memoryinterface module(s) 164 and the cloud processing interface module(s) 166are coupled to the core control module 130. In this embodiment, theinterface modules 164 and 166 are coupled to a cloud peripheral controlmodule 172 that directly couples to the core control module 130.

FIG. 6D is a schematic block diagram of an embodiment of a computingdevice 120 that includes a plurality of computing resources, whichincludes include a core control module 130, a boot up processing module176, boot up RAM 174, a read only memory (ROM) 134, a one or more videographics processing modules 140, one or more displays 48 (optional), anInput-Output (I/O) peripheral control module 144, one or more inputinterface modules 148, one or more output interface modules 150, one ormore cloud memory interface modules 164, one or more cloud processinginterface modules 166, cloud memory 168, and cloud processing module(s)170.

In this embodiment, the computing device 120 includes enough processingresources (e.g., module 176, ROM 134, and RAM 174) to boot up. Oncebooted up, the cloud memory 168 and the cloud processing module(s) 170function as the computing device's memory (e.g., main and hard drive)and processing module.

FIG. 6E is a schematic block diagram of another embodiment of acomputing device 120 that includes a hardware section 180 and a softwareprogram section 182. The hardware section 180 includes the hardwarefunctions of power management, processing, memory, communications, andinput/output. FIG. 6G illustrates the hardware section 180 in greaterdetail.

The software program section 182 includes an operating system 184,system and/or utilities applications, and user applications. Thesoftware program section further includes APIs and HWIs. APIs(application programming interface) are the interfaces between thesystem and/or utilities applications and the operating system and theinterfaces between the user applications and the operating system 184.HWIs (hardware interface) are the interfaces between the hardwarecomponents and the operating system. For some hardware components, theHWI is a software driver. The functions of the operating system 184 arediscussed in greater detail with reference to FIG. 6F.

FIG. 6F is a diagram of an example of the functions of the operatingsystem of a computing device 120. In general, the operating systemfunction to identify and route input data to the right places within thecomputer and to identify and route output data to the right placeswithin the computer. Input data is with respect to the processing moduleand includes data received from the input devices, data retrieved frommain memory, data retrieved from secondary memory, and/or data receivedvia a network card. Output data is with respect to the processing moduleand includes data to be written into main memory, data to be writteninto secondary memory, data to be displayed via the display and/or anoutput device, and data to be communicated via a network care.

The operating system 184 includes the OS functions of processmanagement, command interpreter system, I/O device management, mainmemory management, file management, secondary storage management, errordetection & correction management, and security management. The processmanagement OS function manages processes of the software sectionoperating on the hardware section, where a process is a program orportion thereof.

The process management OS function includes a plurality of specificfunctions to manage the interaction of software and hardware. Thespecific functions include:

-   -   load a process for execution;    -   enable at least partial execution of a process;    -   suspend execution of a process;    -   resume execution of a process;    -   terminate execution of a process;    -   load operational instructions and/or data into main memory for a        process;    -   provide communication between two or more active processes;    -   avoid deadlock of a process and/or interdependent processes; and    -   control access to shared hardware components.

The I/O Device Management OS function coordinates translation of inputdata into programming language data and/or into machine language dataused by the hardware components and translation of machine language dataand/or programming language data into output data. Typically, inputdevices and/or output devices have an associated driver that provides atleast a portion of the data translation. For example, a microphonecaptures analog audible signals and converts them into digital audiosignals per an audio encoding format. An audio input driver converts, ifneeded, the digital audio signals into a format that is readily usableby a hardware component.

The File Management OS function coordinates the storage and retrieval ofdata as files in a file directory system, which is stored in memory ofthe computing device. In general, the file management OS functionincludes the specific functions of:

-   -   File creation, editing, deletion, and/or archiving;    -   Directory creation, editing, deletion, and/or archiving;    -   Memory mapping files and/or directors to memory locations of        secondary memory; and    -   Backing up of files and/or directories.

The Network Management OS function manages access to a network by thecomputing device. Network management includes:

-   -   Network fault analysis;    -   Network maintenance for quality of service;    -   Network access control among multiple clients; and    -   Network security upkeep.

The Main Memory Management OS function manages access to the main memoryof a computing device. This includes keeping track of memory space usageand which processes are using it; allocating available memory space torequesting processes; and deallocating memory space from terminatedprocesses.

The Secondary Storage Management OS function manages access to thesecondary memory of a computing device. This includes free memory spacemanagement, storage allocation, disk scheduling, and memorydefragmentation.

The Security Management OS function protects the computing device frominternal and external issues that could adversely affect the operationsof the computing device. With respect to internal issues, the OSfunction ensures that processes negligibly interfere with each other;ensures that processes are accessing the appropriate hardwarecomponents, the appropriate files, etc.; and ensures that processesexecute within appropriate memory spaces (e.g., user memory space foruser applications, system memory space for system applications, etc.).

The security management OS function also protects the computing devicefrom external issues, such as, but not limited to, hack attempts,phishing attacks, denial of service attacks, bait and switch attacks,cookie theft, a virus, a trojan horse, a worm, click jacking attacks,keylogger attacks, eavesdropping, waterhole attacks, SQL injectionattacks, and DNS spoofing attacks.

FIG. 6G is a schematic block diagram of the hardware components of thehardware section 180 of a computing device. The memory portion of thehardware section includes the ROM 134, the main memory 136, the cachememory 138, the cloud memory 168, and the secondary memory 160. Theprocessing portion of the hardware section includes the core controlmodule 130, the processing module 132, the video graphics processingmodule 140, and the cloud processing module 170.

The input/output portion of the hardware section includes the cloudperipheral control module 172, the I/O and/or peripheral control module144, the network interface module 158, the I/O interface module 146, theoutput device interface 150, the input device interface 148, the cloudmemory interface module 164, the cloud processing interface module 166,and the secondary memory interface module 156. The 10 portion furtherincludes input devices such as a touch screen, a microphone, andswitches. The 10 portion also includes output devices such as speakersand a display.

The communication portion includes an ethernet transceiver network card(NC), a WLAN network card, a cellular transceiver, a Bluetoothtransceiver, and/or any other device for wired and/or wireless networkcommunication.

FIG. 7 is a schematic block diagram of an embodiment of a database thatincludes a data input computing entity 190, a data organizing computingentity 192, a data query processing computing entity 194, and a datastorage computing entity 196. Each of the computing entities isimplementation in accordance with one or more of the embodiments ofFIGS. 5A through 5E.

The data input computing entity 190 is operable to receive an input dataset 198. The input data set 198 is a collection of related data that canbe represented in a tabular form of columns and rows, and/or othertabular structure. In an example, the columns represent different dataelements of data for a particular source and the rows corresponds to thedifferent sources (e.g., employees, licenses, email communications,etc.).

If the data set 198 is in a desired tabular format, the data inputcomputing entity 190 provides the data set to the data organizingcomputing entity 192. If not, the data input computing entity 190reformats the data set to put it into the desired tabular format.

The data organizing computing entity 192 organizes the data set 198 inaccordance with a data organizing input 202. In an example, the input202 is regarding a particular query and requests that the data beorganized for efficient analysis of the data for the query. In anotherexample, the input 202 instructions the data organizing computing entity192 to organize the data in a time-based manner. The organized data isprovided to the data storage computing entity for storage.

When the data query processing computing entity 194 receives a query200, it accesses the data storage computing entity 196 regarding a dataset for the query. If the data set is stored in a desired format for thequery, the data query processing computing entity 194 retrieves the dataset and executes the query to produce a query response 204. If the dataset is not stored in the desired format, the data query processingcomputing entity 194 communicates with the data organizing computingentity 192, which re-organizes the data set into the desired format.

FIG. 8A is a diagram of an example of physical science technicalcategories that include, but is not limited to, the high-levelcategories of communications technology, electrical technology,information technology, energy and power technology, chemicaltechnology, and mechanical & industrial technology. Recall that, ingeneral, physical sciences are regarding the study of the physical,non-living things, in world and/or universe.

FIG. 8B is a diagram of an example of life science technical categoriesthat include, but is not limited to, the high-level categories ofmedical technology, agriculture technology, biological technology,biochemical technology, genetics technology, and ecological technology.Recall that, in general, life sciences are regarding the study of livingthings.

With respect to FIGS. 8A and 8B, the improved computer for technologyorganizes technology based on the physical sciences and life sciences.Within a life science or physical science category, technology isquantified and organized in accordance with market-tech units, which theimproved computer identifies and creates by ingesting and processing upto millions of documents regarding technology, the business oftechnology, the legal protection of technology, the use of technology,the expansion of technology, and/or the relevant information.

The MTUs are mapped into functional diagrams and/or hierarchy diagramsfor ease and clarity of identifying a piece of technology and where itfits in the world of technology and how it affects the technology worldand the business world. The MTU mapping captures and illustrates howtechnology builds on technology. The MTU mapping allows for zooming outon a technology map to get a macroscopic view of the technology and/or azooming in on the technology map to get microscopic views of thetechnology building blocks (which are quantified as MTUs).

The high-level physical science categories can be broken down intosub-categories. For example, FIG. 9A is a diagram of an example ofelectrical technology being broken down into electrical tech itemcategories of computer, circuitry, integrated circuit (IC), software,audio and/or visual devices, and database. Note that this is just anexample and there are more electrical tech item categories. Further notethat an item is a product and/or service that is bought, sold, traded,licensed and/or otherwise consumed by an end-user and/or by an entity ina product supply chain (See FIG. 11B) and/or a service supply chain (SeeFIG. 11A).

As another example, FIG. 9B is a diagram of an example of communicationtechnology item categories that include television, radio, the Internet,wireless communications, wired communications, and opticalcommunications. Note that this is just an example and there are morecommunication tech item categories.

As a further example, FIG. 9C is a diagram of an example of informationtechnology (e.g., the use of systems for storing, retrieving, processingand/or sending digital information) item categories that includes datasystem architecture, software platform, data communication networks,data synchronization, data storage, and specific data analytics. Notethat this is just an example and there are more information technologyitem categories.

As yet a further example, FIG. 9D is a diagram of an example of energy &power technology item categories that includes solar, wind, batteries,nuclear, and power distribution. Note that this is just an example andthere are more energy and power tech item categories. Further note thateach of the tech item categories of FIGS. 9A through 9D include one ormore layers of further sub-categories.

While not shown in FIGS. 9A through 9D, the following provides examplesof sub-categories for the other high-level physical and life sciencecategories.

-   -   A few examples of the practical purposes of mechanical &        industrial technology include manufacturing, building        construction, building materials, and transportation        infrastructure.    -   A few examples of the practical purposes of medical technology        include diagnosis, surgical, pharmaceutical, health monitoring,        genetic engineering, and treatment.    -   A few examples of the practical purposes of chemical technology        include plastics, pharmaceuticals, materials, and reactions.    -   A few examples of the practical purposes of transportation        technology includes global positioning satellite (GPS), flight,        vehicles, collision protection for living and/or non-living        things, and automation of transportation.    -   A few examples of the practical purposes of agriculture        technology include robotic planting/weeding/harvesting, watering        control, pest control, and soil content control.    -   A few examples of the practical purposes of biological        technology include synthesizing insulin and/or other human        biologicals, DNA profiling, stem cells, and genome analysis.    -   A few examples of the practical purposes of information        technology include establish a software platform, establish a        data communications network, establish data synchronization of a        data set, establish data storage of a data set, establish        specific analytics of a data set.

FIG. 10A is a Venn diagram of communication technology, informationtechnology, and electrical technology. As shown, there is technicaloverlap between the three tech categories. For example, a computingdevice would be within the intersection of the three technologycategories. Note that at the center of the Venn diagram is dataprocessing. All three of the technology categories rely on dataprocessing and so many of the technology advancements made, and beingmade, in these tech categories depends on inventive, reliable, andrepeatable data processing.

FIG. 10B is a Venn diagram of communication technology, informationtechnology, and electrical technology with energy & power technology.The combination of communication, information, and electricaltechnologies overlap with the energy & power technology. At the centerof the overlap is data processing.

FIG. 10C is a Venn diagram of communication technology, informationtechnology, and electrical technology with chemical technology. Thecombination of communication, information, and electrical technologiesoverlap with the chemical technology. At the center of the overlap isdata processing.

FIG. 10D is a Venn diagram of communication technology, informationtechnology, and electrical technology with mechanical & industrialtechnology. The combination of communication, information, andelectrical technologies overlap with the mechanical & industrialtechnology. At the center of the overlap is data processing.

FIG. 10E is a Venn diagram of communication technology, informationtechnology, and electrical technology with medical technology. Thecombination of communication, information, and electrical technologiesoverlap with the medical technology. At the center of the overlap isdata processing.

FIG. 10F is a Venn diagram of communication technology, informationtechnology, and electrical technology with agriculture technology. Thecombination of communication, information, and electrical technologiesoverlap with the agriculture technology. At the center of the overlap isdata processing.

FIG. 10G is a Venn diagram of communication technology, informationtechnology, and electrical technology with biological technology. Thecombination of communication, information, and electrical technologiesoverlap with the biological technology. At the center of the overlap isdata processing.

FIG. 10H is a Venn diagram of communication technology, informationtechnology, and electrical technology with biochemical technology. Thecombination of communication, information, and electrical technologiesoverlap with the biochemical technology. At the center of the overlap isdata processing.

FIG. 101 is a Venn diagram of communication technology, informationtechnology, and electrical technology with genetics technology. Thecombination of communication, information, and electrical technologiesoverlap with the genetics technology. At the center of the overlap isdata processing.

FIG. 10J is a Venn diagram of communication technology, informationtechnology, and electrical technology with ecological technology. Thecombination of communication, information, and electrical technologiesoverlap with the ecological technology. At the center of the overlap isdata processing.

FIG. 11A is a schematic block diagram of an example of a service supplychain that includes three main sections of service production, servicedistribution, and service use. As used herein, a “service” shall meanthe use of a commercial and/or proprietary product(s) for the benefit ofan end user and/or other entity in a service supply chain. The servicecan be performed by the service provider for the targeted user (e.g.,the end user or an entity in the supply chain) or the service is aself-service. As is also used herein, a “product” is physical or virtualthing that is bought, sold, leased, consumed, etc. by an end user and/orany entity in a product supply chain.

An end-user is a person or business entity that can access a servicedirectly from the company offering the service or access through theservice an intermediary (e.g., a service retailer or serviceaggregator). The intermediary obtains the right to offer the service toend users directly from the company providing the service or through aservice wholesaler.

A service (e.g., software as a service, storage as a service, streamingcontent service, etc.) includes one or more tiers of services. The tiersof service include tier services provided by others and products thatenable the performance of a service tier. For example, a streamingcontent service a communication service that delivers streaming contentto an end user, a data storage services that stores the content, and adigital rights management service for authorized distribution of thecontent. Each service and each service of a tier is represented by itsown market-tech unit (MTU).

FIG. 11B is a schematic block diagram of an example of a product supplychain that includes three main sections of product production, productdistribution, and product use. An end-user is a person or businessentity that obtains (e.g., purchases, leases, rents, etc.) a productdirectly from the company offering the product or access through aproduct intermediary (e.g., a retailer, a broker, a leasing agent, arental entity, etc.). The product intermediary obtains the right tooffer the product to end users directly from the company selling theproduct or through a wholesaler and/or distributor.

A product includes one or more tiers of products. Each product of eachtier is represented by its own market-tech unit (MTU). Some products areidentified as fundamental elements of other products. Forcommunications, electrical, and information technologies, fundamentalproducts include hardware components, hardware circuits, and hardwarecircuit blocks. An example of fundamental MTUs is discussed withreference to FIG. 40 .

FIG. 12A is a schematic block diagram of an example of a high-leveltechnology relational map. As mentioned, market-tech units (MTUs)represent pieces of technology, which range from a fundamental elementMTU that is linked all the way up to a high-level MTU (e.g., ahigh-level technology category). In this diagram, a root tier MTU forphysical sciences includes tier 1 MTUs for communications technology,information technology, electrical technology, energy & powertechnology, chemical technology, and mechanical & industrial technology.As is also shown, a root tier MTU for life sciences includes tier 1 MTUsfor medical technology, agriculture technology, biological technology,biochemical technology, genetics technology, and ecological technology.

Other root tier MTUs include product design & development, productmanufacturing, product distribution, product use, service design &development, service manufacturing, service distribution, and serviceuse. These root MTUs are linked to other root MTUs to provide ahigh-level technology map based on MTUs. The technology map is routinelychanging to correspond to changes in technology. New technologiesemerge, old technologies fade away, and existing technologies evolve,expand, and transform.

FIG. 12B is a schematic block diagram of an example of a technologyrelational map for a cell phone based on tiers of inclusion MTUs andtiers of composition MTUs. As used herein, inclusion is regarding one ormore higher tiers and composition is regarding one or more lower tiers.In this example, the initially selected MTU is that of a cell phone. Thecell phone is part of the higher tier MTU of the portable computingdevice; the portable computing device is part of the higher tier MTU ofcomputing devices, which is part of the higher tier MTU ofcommunications, information, and electrical (CIE) technologies.

Parallel MTUs of a cell phone include the MTUs of smart watches,laptops, tablets, and two-way radios. The quantifying of technologiesMTUs will be described in detail with reference to subsequent figures.

The cell phone MTU is composed of lower tier MTUs of input/outputhardware, processing, memory, communication, and power management. Theinput/output hardware MTU is composed of lower tier MTUs of inputinterface & input devices, output interface & output devices, 2^(nd)memory interface & second memory devices, and communication interface &communication devices. The input interface & input devices MTU iscomposed of the lower tier MTUs of touchscreen, microphone, camera, andswitches/buttons. The touchscreen MTU is composed of the lower tier MTUsof touch screen controller and touch sensors. The touch screencontroller MTU is composed of lower tier MTUs of sensor circuit andprocessing circuit. The sensor circuit MTU is composed of the lower tierMTUs of sense circuit, drive circuit, digital filter, and digital touchprocessing. The sense circuit MTU is composed of the lower tier MTUs ofop amp, voltage reference, and analog to digital converter (ADC).

The cataloging and linking of MTUs creates a technology map that can bezoomed out to a “10,000 foot view” of communications, information, andelectrical technologies and that can be zoomed in to a “backyard view”of the components of a sense circuit.

FIGS. 13A through 13E are schematic block diagram of embodiments ofitems that include one or more market-tech units (MTUs). FIG. 13A is aschematic block diagram of an item that includes one market-tech unit(MTU). An item is a physical and/or virtual product and/or service thatis exchanged from one entity to another in a supply chain of FIG. 11A orof FIG. 11B and/or a distinguishable portion of such a physical and/orvirtual product and/or service. In an example, an item is a resistor. Inanother example, an item is an airplane.

FIG. 13B is a schematic block diagram of an item that includes two ormore market-tech units (MTUs).

FIG. 13C is a schematic block diagram of an item that includes two tiersof MTUs, with one tier including lower tier MTUs.

FIG. 13D is a schematic block diagram of an item that includes threetiers of MTUs, with each tier including lower tier MTUs.

FIG. 13E is a schematic block diagram of an item that includes aplurality of tiers of MTUs, with each tier including lower tier MTUs.

FIG. 14A is a schematic block diagram of an example of a market-techunit (MTU) composition map. In this example, an item has an MTU at tierI, and is composed a plurality of other MTUs from tiers i-1, i-2, i-3,and so on to i-“x”, where x is 4 or more. Some of the lower tier MTUsare also composed of other MTUs. In total, this item is composed of atotal of 32 other MTUs; MTUs 1, 3, 6, 10, 13, 15, 18, and 22 from tieri-2; MTUs 2, 8, 14, and 20 from tier i-2; MTUs 5 and 17 from tier i-3;and MTU x1 from tier i-x.

MTU 3 of tier i-1 is at least partially composed of MTU 4 from tier i-2;MTU 6 of tier i-1 is at least partially composed of MTU 7 from tier i-3;MTU 8 of tier i-2 is at least partially composed of MTU 9 of tier i-3;MTU 10 of tier i-1 is at least partially composed of MTU 11 of tier i-2,which is at least partially composed of MTU 12 of tier i-3; MTU 13 oftier i-1 is at least partially composed of MTU x2 of tier i-x; MTU 14 oftier i-2 is at least partially composed of MTU x3 of tier i-x; MTU 15 oftier i-1 is at least partially composed of MTU 16 of tier i-2, which isat least partially composed of MTU x4 of tier i-x; MTU 17 of tier i-3 isat least partially composed of MTU x5 of tier i-x; MTU 18 of tier i-1 isat least partially composed of MTU 19 of tier i-3, which is at leastpartially composed of MTU x6 of tier i-x; MTU 20 of tier i-2 is at leastpartially composed of MTU 21 of tier i-3, which is at least partiallycomposed of MTU x7 of tier i-x; and MTU 22 of tier i-1 is at leastpartially composed of MTU 23 of tier i-2, which is at least partiallycomposed of MTU 24 of tier i-3, which is at least partially composed ofMTU x8 of tier i-x.

The composition map is expressed graphically as a functional compositiondiagram and/or as a hierarchy composition diagram in the MTU record forthe item. From a diagram, each MTU is selectable to view its MTU record,which will be described in greater detail with reference to subsequentfigures.

FIG. 14B is a schematic block diagram of another example of amarket-tech unit (MTU) composition hierarchy diagram for an electricalitem. The item is composed of sub-item (SI) MTUs, operational circuit(OC) MTUs, functional circuit (FC) MTUs, building block circuit (BBC)MTUs, and circuit component (CC) MTUs. A higher tier MTU may include oneor more MTUs of one or more lower tiers.

FIG. 15A is a schematic block diagram of an example of a market-techunit (MTU) inclusion and composition relationships. With respect to anMTU of interest, inclusion is referring to higher tier MTU andcomposition is referring to lower tier MTUs. For example, the cell phoneof FIG. 12B has a composition relationship with the input/output HW, theprocessing HW, the memory, the communication HW, and power management.As another example, the cell phone of FIG. 12B has an inclusionrelationship with portable computing devices, which has an inclusionrelationship with computing devices, which has an inclusion relationshipwith CIE technology.

FIG. 15B is a schematic block diagram of another example of amarket-tech unit (MTU) inclusion relationship for the electrical item ofFIG. 14B. In this diagram, a circuit component (CC) MTU may be includedin other circuit component (CC) MTUs; may be included in building blockcircuit (BBC) MTUs; may be included in functional circuit (FC) MTUs; maybe included in operational circuit (OC) MTUs; may be included insub-item (SI) MTUs; and may be included in item MTUs.

A building block circuit (BBC) MTU may be included in other buildingblock circuit (BBC) MTUs; may be included in functional circuit (FC)MTUs; may be included in operational circuit (OC) MTUs; may be includedin sub-item (SI) MTUs; and may be included in item MTUs.

A functional circuit (FC) MTU may be included in other functionalcircuit (FC) MTUs; may be included in operational circuit (OC) MTUs; maybe included in sub-item (SI) MTUs; and may be included in item MTUs.

An operational circuit (OC) MTU may be included in other operationalcircuit (OC) MTUs; may be included in sub-item (SI) MTUs; and may beincluded in item MTUs.

A sub-item (SI) MTUs may be included in other sub-item (SI) MTUs; andmay be included in item MTUs. An item MTU may be included in other itemMTUs.

FIG. 15C is a schematic block diagram of another example of amarket-tech unit (MTU) composition relationships. In this diagram, anitem may be composed of one or more circuit component (CC) MTUs, one ormore building block circuit (BBC) MTUs, one or more functional circuit(FC) MTUs, one or more operational circuit (OC) MTUs, one or moresub-item (SI) MTUs; and/or one or more other item MTUs.

A sub-item MTU may be composed of one or more circuit component (CC)MTUs, one or more building block circuit (BBC) MTUs, one or morefunctional circuit (FC) MTUs, one or more operational circuit (OC) MTUs,and/or one or more other sub-item (SI) MTUs.

An operational circuit (OC) MTU may be composed of one or more circuitcomponent (CC) MTUs, one or more building block circuit (BBC) MTUs, oneor more functional circuit (FC) MTUs, and/or one or more otheroperational circuit (OC) MTUs.

A functional circuit (FC) MTU may be composed of one or more circuitcomponent (CC) MTUs, one or more building block circuit (BBC) MTUs,and/or one or more other functional circuit (FC) MTUs.

A building block circuit (BBC) MTU may be composed of one or morecircuit component (CC) MTUs, and/or one or more other building blockcircuit (BBC) MTUs. A circuit component (CC) MTU may be composed of oneor more other circuit component (CC) MTUs. For CIE (communications,information, electrical) technologies, a circuit component includesfundamental hardware components, fundamental hardware circuits, and/orfundamental hardware circuit blocks; examples of which are discussedwith reference to FIG. 40 .

FIG. 16A is a schematic block diagram of an example of a softwaremarket-tech unit (MTU) composition relationship. In this diagram, aprogram (PR) MTU is composed of one or more sub-routine (SR) MTUs andone or more operational instructions (01) MTUs of a programming language(PL) MTU. A sub-routine may include one more tiers of othersub-routines. Note that operational instructions MTUs are fundamentalMTUs and are included in composition diagrams, but typically will notinclude inclusion diagrams. Further note that a program is a softwarealgorithm that includes system applications, user applications, andoperating system functions, and/or portions thereof.

FIG. 16B is a schematic block diagram of another example of a softwaremarket-tech unit (MTU) composition relationship. In this example, theprogram or application MTU includes, but is not limited to, operatingsystem, voice recognition, video processing, audio processing, touchsense processing, user applications, artificial intelligence (AI)applications, system applications, machine learning (ML) applications,and/or utility applications.

A sub-routine MTU tier includes a logic routine, a mathematical routine,data compression, a look-up routine, time calculation, etc. Anoperational instruction set MTU includes, but is not limited to, store,add, load, AND, OR, clear, convert, compare, subtract, multiply,divided, increment, etc. A programming language MTU includes C++,Python, JavaScript, Java, C, GO, R, swift, PHP, MATLAB, etc.

FIG. 17 is a flow diagram of an example of technology development,business development, patent protection of the technology, and businesssuccess. When a business contemplates developing a new technology and/orwhen investment companies contemplate in companies developing a newtechnology, the unique value proposition(s) of the technology, itsmarket opportunities, and market adoption are studied and evaluated ingreat detail.

How long will it take to develop the technology? How much money will itcost? What is the market opportunity for the technology (serviceobtainable market)? What is the estimated return on investment? Theanswers to these questions dictate whether a company will develop atechnology and/or whether it will get funding to the develop thetechnology.

In accordance with a re-engineered patent process and the improvedcomputer disclosed herein, patent protecting a technology now receivesequal scrutiny. Based on the phases of development of the technology andexisting patent landscape, the improved computer calculates a patentprotection opportunity for the technology. The technology is quantifiedby one or more market-tech units (MTUs).

The improved computer then calculates what can be owned. In thisinstance, ownership means patent position for the technology withrespect to others' patent position for the technology. A superior patentposition places the patent holder in a most favorable position withrespect to others in a patent dispute regarding the technology. As partof calculating the patent protection opportunity and what can be owned,the improved computer determines, based on the phase of development, howmuch patenting of the technology already exists, or should exist, andhow much patenting of the technology is future forecasted.

If a good amount of patenting already exists and the present companyowns little of the existing patents, the improved computer determineswhat patent position can be obtained for various levels of patenting. Itmay be impossible to obtain a superior patent position no matter thelevel of patenting going forward if there are too many existing patents.

From the patent protection opportunity and the “what can be owned”calculations, the improved computer determines the value of thetechnology based on the patent position that can be obtained. The valuecalculation factors in the market opportunity, market adoption (actualand/or forecasted), sustained market success (actual and/or forecasted),and the cost to patent protect the technology. If the calculations arefavorable, the improved computer generates a patent protection plan.

With patent protection in place, a company is much more likely to obtainsustained market success than without patent protection. If productsand/or services embodying the technology take market share from othersand/or creates a new market opportunities, others will want to stop theloss of market share and some others will want to capitalize on the newmarket opportunities. A good patent position will help protect the newlyacquired market share.

Unfortunately, too many companies and investors barely consider thepatent protection opportunity; it is often treated as a check-markanalysis. The company has patents, check. While the check-mark approachto patenting technology can get to market adoption, it is highlyunlikely sustained success can be reached; especially if the technologyis the primary market differentiator. In this instance, too much of thetechnology was not patent protected and is thus free for others to use.When this occurs, the value of the technology is greatly diminished fromwhat it should be if the technology were properly patent protected.

FIG. 18 is a logic diagram of an example of value of patent protectedtechnology (one or more market-tech units [MTUs]). This diagram buildson the discussion of FIG. 17 and further emphasizes the value of asuperior patent position. The first box states that patents preventothers from unauthorized use of patented technology. In addition, ifnobody wants to use a patented technology, then the technology andpatents protecting it have little to no value.

If another entity or person is using the patented technology withoutauthorization, the patent holder will have to assert its patents againstthe infringing entity if the patent holders wants the unauthorized useto be stopped and/or to be compensated for the unauthorized use. One wayto assert patents is through patent litigation in which one to severalpatents are asserted.

For a patent holder that built its patent portfolio using the improvedcomputer for technology, the patent holder has numerous patents toassert of which, a few are selected for a variety of litigation reasons(e.g., notice, priority dates, claim coverage, clean file wrapperhistories, etc.). For small companies that didn't use the improvedcomputer for technology only owns a few patents, which they assert. Forlarge companies that didn't use the improved computer for technology,they shifted through their patents to identify assertable patents.

Since over 95% of patent litigation cases settle before trial,eventually the patent holder and the infringing entity will enter into alicensing negotiation. Note that of the 5% of patent cases that do go totrial, most of them end in settlement unless that patents are found tobe invalid or not infringed.

In licensing negotiations between two practicing entities, theirrespective patent portfolios come into play. While a few patents can beused to begin a patent assertion process, it is the patent portfoliosthat dictate the outcome of licensing negotiations. Basically, theentity having the superior patent position with respect to the otherwins; it will receive money from the other entity. A superior patentposition is a first practicing entity having more impact through patentprotected technology on the other practicing entity than their patentprotected technology impacts has on the first entity.

The more favorable the licensing negotiations (i.e., the more favorablethe patent position) the more likely the practicing entity will haveon-going business success. Conversely, the less favorable the licensingnegotiations, the more likely the practicing entity will have on-goingbusiness issues and challenges.

FIG. 19 is a diagram of an example of a full spectrum of invention typesfor patenting to patent protect a technology (one or more market-techunits [MTUs]). As part of the re-engineered patent process and, as partof the functionality of the improved computer for technology, a fullspectrum of invention types are analyzed for inclusion in anarchitectural plan for patent protecting an MTU (e.g., a quantifiedtechnology).

The invention types include fundamental inventions, commerciallynecessary inventions, and commercial expansion inventions as werediscussed with reference to the conventional patent process. Incontrast, the relative quantities of each will be significantly higherfor the re-engineered patent process than for the conventional patentprocess. This occurs because the re-engineered patent process overcomesthe engineer driven invention disclosure step, the too “me” focusedinventions, the too “now” focused inventions, the too “many goodinventions not being patented” issue, the annually budget focus, theindividual invention focus, and the patent application preparation andprosecution variance of the conventional patent process. The improvedcomputer further factors in design-around inventions.

In addition, the improved computer for technology, in accordance withthe re-engineered patent process, evaluates other invention types todetermine the value they add to patent protecting the technology. Theother invention types include new fundamental inventions, new uses offundamental inventions, commercial expansion of new use inventions,vertical integration inventions, horizontal integration inventions,potential acquirer integration inventions, competitor speed bumpinventions, potential standard essential inventions, and potentialstandard non-essential but commercially essential inventions.

The new fundamental inventions include inventions that expand the scopeof the fundamental concepts beyond me and now (what is currently beingdeveloped for inclusion in a product and/or service). The improvedcomputer uses one or more ML (machine learning) and/or AI (artificialintelligence) programs to calculate and report on new fundamentalinventions. The one or more programs will be discussed with reference tosubsequent figures.

The new uses of fundamental inventions include new ways to use theoriginal fundamental inventions and the new fundamental inventions. Theimproved computer uses one or more ML and/or AI programs to calculateand report on new uses of fundamental inventions. The one or moreprograms will be discussed with reference to subsequent figures.

The commercial expansion of new use inventions include inventions thatexpand on the original commercially necessary inventions, the originalcommercial expansion inventions, and on uses of the new fundamentalinventions. The improved computer uses one or more ML and/or AI programsto calculate and report on commercial expansion of new use inventions.The one or more programs will be discussed with reference to subsequentfigures.

The vertical integration inventions include inventions that wouldintegrate the present MTU into one or more MTUs of a higher tier and/orthat would integrate a lower tier MTU into the present MTU. The improvedcomputer uses one or more ML and/or AI programs to calculate and reporton vertical integration inventions. The one or more programs will bediscussed with reference to subsequent figures.

The horizontal integration inventions include inventions that wouldintegrate the present MTU into one or more MTUs of the same tier and/orthat would integrate a same tier MTU into the present MTU. The improvedcomputer uses one or more ML and/or AI programs to calculate and reporton horizontal integration inventions. The one or more programs will bediscussed with reference to subsequent figures.

The potential acquirer integration inventions include inventions wouldintegrate the present MTU into one or more MTUs of the potentialacquirer. The improved computer uses one or more ML and/or AI programsto calculate and report on potential acquirer integration inventions.The one or more programs will be discussed with reference to subsequentfigures.

The competitor speed bump inventions include inventions that target afuture technology path of a competitor regardless of whether the futuretechnology path is part of a company's present roadmap. These inventionsare intended to provide leverage is subsequent negotiations with thetargeted competitor(s). The improved computer uses one or more ML and/orAI programs to calculate and report on competitor speed bump inventions.The one or more programs will be discussed with reference to subsequentfigures.

The potential standard essential inventions include inventions thatwould likely be adopted by a standard if such a standard were to beformed. Typically, essential patents for a standard have to be licensedat a reasonable and non-discriminatory (RAND) royalty rate. The improvedcomputer uses one or more ML and/or AI programs to calculate and reporton potential standard essential inventions. The one or more programswill be discussed with reference to subsequent figures.

The potential standard non-essential but commercially essentialinventions include inventions that would likely not be essential for astandard if such a standard were to be formed. These inventions,however, would most likely be needed to make a commercially viablestandards compliant product and would not be subject RAND royalty rates.The improved computer uses one or more ML and/or AI programs tocalculate and report on potential standard non-essential butcommercially essential inventions. The one or more programs will bediscussed with reference to subsequent figures.

FIG. 20 is a schematic block diagram of an example of a re-engineeredpatent process 220. The improved computer leverages the re-engineeredpatent process to effectively and efficiently quantifying a technologyin terms of one or more market-tech units (MTUs), to generate anarchitectural plan for patent protecting the technology, to generate useopportunities reports regarding the technology, to generate a reportregarding the lifelong value of the technology, to track execution ofthe architectural patent, and to ensure quality execution of thearchitectural plan.

The improved computer for technology generates, using one or more MLand/or AI programs, a multiple year architectural plan for an MTU basedon a balancing of a desired patent position and a desired patent spendand based on x desired The multiple year architectural plan drives usesof the patent protected MTU. For multiple MTUs of interest, the improvedcomputer generates a unique architectural plan for each MTU. In anembodiment, the improved computer further balances the desired patentspend and desired patent position among the multiple MTUs.

The desired patent position is with respect to others regarding a patentdispute involving the technology and can range from weak to superior. Asuperior patent position is one in which the patent holder has asuperior patent position with respect to all others involved with thetechnology. A weak paten position is one in which the patent holder hasan inferior patent position with respect to most, if not all, othersinvolved with the technology.

The desired patent spend is based on a desired ROI over the life theMTU. The ROI is the anticipated value of the MTU divided by the patentspend. The improved computer generates, using one or more ML and/or AIprograms, a year-by-year valuation report for the MTU over the life ofthe MTU. The life of an MTU includes one or more generations.

The desired future uses of the patent protected MTU include marketleverage, asset value, assertion, sale, and/or standards. Essentially,the improved computer generates a report regrading of how the patentprotected MTU can be used in the future based on the level of patentprotection. For many companies, the most important use of a patentprotected MTU is maximizing the company's valuation by maximizing thevalue of the MTUs “owned” via patent protection by the company.

The multiple year architectural plan drives the remainder of the patentprocess. It identifies, on a year-by-year basis, quantities ofinventions to patent protect for each of the technical challenges of theMTU, the invention type breakdown for each technical challenge, where toseek patent protection, and the manner of patent protection (e.g.,provisional patent application, non-provisional patent application, PCTapplication, a bundled patent application, and/or a subsequent filingpatent application). With the invention types, invention quantities, andinvention to technical challenge affiliations established, an activeinvention disclosure process is employed to pull specific inventionsfrom engineers and/or to stimulate further inventing.

The multiple year architectural plan drives the filing decisionsregarding specific inventions. Since specific inventions are pulled fromengineers and/or from inventing sessions, the disclosed inventions arein accordance with the multi-year plan and are targeted to protectcertain innovations of the MTU (e.g., address technical challenges of aquantified technology). As such, the filing decision step shifts from anannual budget driven and individual invention focus decision of theconventional patent process to a portfolio fit decision at thetechnology level of the re-engineered patent process.

The multiple year architectural plan drives the patent applicationpreparation step since it prescribes the manner of patent protection forcategories of inventions (e.g., types and technical challenges). Inaddition, the improved computer includes one or more ML and/or AIprograms regarding quality assurance of patent application preparationand prosecution.

The multiple year architectural plan drives subsequent filing decisions(e.g., the filing of a continuation application, a divisional patentapplication, a continuation-in-part patent application, or legalplaceholder continuation patent application for an allowed patentapplication). It also drives maintenance decisions regarding issuedpatents. Since every patent filed was in accordance with the plan, thereshould be very few patents for which maintenance fees are not paid.

As the improved computer routinely ingest more data, it adjusts thearchitectural plan accordingly. For example, if the ingested data isindicated a shift in use of a technology, the improved computer adjuststhe plan to ensure the desired patent position is obtained for the shiftin use of the technology.

FIG. 21A is a schematic block diagram of another embodiment of are-engineered patent process. In this example, the re-engineered patentprocessing includes the main steps of desired usage of patents, marketdemand, architectural plan, MTU patent portfolio, and patentprocurement. The uses include injunctive relief (enjoin use, sale, offerfor sale, etc.), licensing revenue source, cross licensing negotiationleverage, influencing standards, market share protection and leverage,as an asset valuation generator, selling patents, and/or establishingnew business entities via a spin-off or joint venture.

Market demand, actual and forecasted, is a significant factor ingenerating the architectural plan. Based on the premise that a patentonly has value if another wants to use the patented invention, marketdemand for patented technology is essential to put forth the effort todevelop, productize, and protect a technology, which identified via oneor more MTUs.

The inventions currently patent protected as recording the MTU patentportfolio helps shape the architectural plan or at least a year or twoof the plan. For example, if one technical challenge is on track for thedesired number of inventions to protect, a second technical challenge isahead of pace for protecting the desired number of inventions, and athird technical challenge is behind pace for protecting the desirednumber of inventions protect, the improved computer adjusts, via an MLand/or AI program, the near term portion of the plan to increase thepace of patent protecting inventions regarding the third technicalchallenge, decreasing the pace of patent protecting inventions regardingthe second technical challenge, and maintaining the pace of patentprotecting inventions regarding the first technical challenge.

Continuing with the preceding example, the improved computer wouldraise, per the ML and/or AI program, the threshold for seeking patentprotection for inventions regarding the third technical challenge. Theimproved computer would also lower, per the ML and/or AI program, thethreshold for seeking patent protection for inventions regarding thesecond technical challenges. The improved computer would furthergenerate, via the ML and/or AI program, a report to emphasize increasinginvention harvesting sessions and/or inventing sessions regarding thesecond technical challenge.

The patent procurement section includes the elements of targetedinventions, advanced inventing, invention harvesting, decide, prepare &file patent applications, prosecuted patent applications, issuespatents, subsequent application filing decision, and prepare and filesubsequent patent applications. The targeting inventions are identifiedin the architectural plan by quantity, type, and technology challengesand can be pulled from engineers during invention harvesting sessions(e.g., query engineers in particular technology areas what they areworking on, have worked on, or will be working on regarding a technicalchallenge) and/or advanced inventing session (e.g., identify one or moreproblems of a technical challenge and invent solutions to the problem).

FIG. 21B is a schematic block diagram of an example of data for are-engineered patent process for effective and efficient patentprotection, use, and/or value of a technology (one or more market-techunits [MTUs]). How the improved computer uses the data listed in thisFigure is discussed in greater detail with reference to one or more theFigures.

In this example, there are three main data categories used by theimproved computer to support the re-engineered patent process. The threemain data categories are cost factors, technology protection factors,and market impact factors.

The cost factor category includes sub-categories of quality of patentprotection, proactive invention identification (inv. ID), filingdecision, patent application, patent prosecution, desired leverage, andpatent landscape. The quality of patent protection for an MTU includesdata regarding total number of inventions for an MTU, the ideal numberof inventions to patent protect for the MTU (part of total number), thetechnical challenges of the MTU, the invention types, number of placeholder inventions, the number of issued patents, and the number ofpending patent applications.

The proactive invention identification for an MTU includes dataregarding the use of invention harvesting sessions and the use ofadvanced inventing sessions. The filing decision for an MTU includesbusiness impact (e.g., market analysis, financial analysis, businessobjectives, technology details, competition, etc.) and patent portfoliofit (e.g., review of plan as to where an invention fits).

The desired leverage sub-category includes a superior patent position, amoderate patent position, a weak patent position, and no patentposition. This sub-category applies to the cost factor category and thetechnology protection factors category.

The patent landscape sub-category includes previous generation quantityof inventions patent protected, competitor previous generation patentand technology data, estimated current generation level of innovation,estimated competitor current generation patent and technology data,estimated next generation level of innovation, and estimated competitornext generation patent and technology data. This sub-category applies tothe cost factor category and the technology protection factors category.

The existing patents sub-category includes generation to generationcomparison of the level of disruption, where MT is a better mouse trap,EVOL is evolutionary, and REV is revolutionary. These levels ofdisruption were discussed with reference to one or more previousFigures. The invention types sub-category list the invention types forFIG. 19 and expand on them to include generational information.

The portfolio factors sub-category includes remaining life of patents,breadth of coverage of the patents, balance of patent coverage of atechnical challenge and among the technical challenges, a pendingapplication to issued patent ratio, an issued patent score, and aquality of patents score. The phase of a generation sub-categoryincludes create, deploy, optimize, mature, and decline.

The level of disruption category, which spans the technology protectionfactors category and the market impact factors category, includesincremental, better mouse trap, evolutionary, and revolutionary. Themarket potential sub-category includes market data, market CAGR, newtech (MTU) market takeover factor, takeover time frame, new tech marketexpansion, and market expansion time frame.

FIG. 22 is a flow diagram of an example of a generating an architecturalplan for patent protecting a technology (a market-tech unit [MTU)]. Thediagram is colored based on the nature of a block. Light gray-greenrepresents a document gathering, document partitioning for dataextraction, and data organization performed by the improved computer;the light gray represents a forecasting function performed by theimproved computer, black represents an output produced by the improvedcomputer, dark blue-gray represents a user input received by theimproved computer, and dark grey-green represents analysis and/orcalculations performed by the improved computer.

For the improved computer to generate an architectural plan that mapsout what inventions to protect, when, and how (e.g., inventionquantities, types, timing, and filing approach), and to generate ayear-by-year report regarding the value of the MTU and patent ROI, theimproved computer requires data regrading, desired patent position,desired patent spend, market impact of the MTU, desired uses of thepatented MTU, relevant MSBT (marketing, sales, business, technology)documents, technology expansion forecast, patent data (existing and/orforecasted annotated patents and/or patent terms), and MTU techboundaries (which include features, unique value propositions, technicalchallenges, and may further include problems).

The desired patent position and desired patent spend are user inactiveinputs, which if left blank, the improved computer uses the desiredpatent position of superior with no limit on the patent spend. The user,via an authorized user device, has the option of accepting the patentposition and/or the patent spend. If both are accepted, the improvedcomputer generates the architectural plan, which includes output reportsfor active inventing sessions regarding targeted inventions and forfiling decisions for pursed inventions.

If the user, via the authorized user device, reject the patent spend,the user can enter a new desired patent spend. With the spend as aconstraint, the improved computer adjusts the patent position until itgenerates a new architectural plan that meets the patent spendconstraint. The improved computer provides the user device with theadjusted patent position and the report on valuation and ROI. If theuser accepts the new patent position, the improved computer generatesthe architectural plan and corresponding reports.

If the new patent position is not accepted, the user, via the authorizeduser device, adjusts the patent spend and/or the desired patent spenduntil an acceptable compromised is reached.

FIG. 23 is a flow diagram of another example of generating a patentprotection plan for a technology (one or more market-tech units [MTUs)].In this diagram, the desired uses, desired patent position, andestimated value of the MTU drive the long-term architectural plan. Theplan enables active invention identification, technology based filingdecisions, and answers the question of how many inventions should bepatent protected, which, by not enabling, are significant drawbacks ofthe conventional patent process.

Unlike the conventional patent process, the re-engineered patent processyields a right sized patent portfolio that is balanced, that has nowaste, and that maximizes value of the patented technology. There-engineered patent process also enables routine calculations of howwell a technology is being patent protected; starting from day 1. Do nothave to wait until the patents are needed, as is done in theconventional patent process, to determine the quality and level ofpatent protection.

FIG. 24 is a schematic block diagram of a further embodiment of animproved computer for technology 70. The improved computer 70 includesthe MSBTP (marketing, sales, business, technology, patents) datagathering section 72, which, in an embodiment, is implemented via one ormore computing entities; system databases 74, each of which, in anembodiment, is implemented as per FIG. 7 ; a data processing section 76,which, in an embodiment, is implemented via one or more computingentities; a subscription based user interface section 78, which, in anembodiment, is implemented via one or more computing entities; and asubscription pricing section 80, which, in an embodiment, is implementedvia one or more computing entities.

As will be discussed in greater detail with reference to subsequentfigures, the MSBTP data gathering section 72 includes one or moreco-processors for ingest documents, for classifying the documents withan MTU classification, and for identifying new MTUs from the documents.Relevant documents are stored in a system databases 74, which includesan MSBTP database (DB) 262, an MTU database 264, a patent term database266, and an annotated (ann.) patent database 268.

The data processing section 76 includes one or more co-processors for anreport output function; for a select an MTU function; for an expand anMTU function; for an expand market opportunities function; for analysisand valuation of an MTU with respect to existing patents; for analysisand valuation of an MTU with respect to future forecasted patents; forpatent portfolio development based on MTUs; for patent applicationpreparation and prosecution; and for patented MTU exploitation (e.g.,patent uses and/or constructive notice). The data processing section 76also includes private developing portfolio databases and a databaseinterface unit 260 (which provides the data processing section access tothe system databases).

In operation, the MSBTP data gathering section 72 routinely ingestsdocuments (millions over time) and processing them to extract MTUinformation. The MTU information corresponds to data regarding anexisting MTU and/or to data to identify a new MTU. For each ingesteddocument to be saved (e.g., the document has at least one piece ofinformation (regardless of how small) pertaining to an existing MTU or apotential new MTU, the MSBTP data gathering section 72 creates adatabase entry request.

For example, when the document is an issued patent or a pending patentapplication, the MSBTP data gathering section 72 generates an annotatedpatent database entry request for the patent or application that hasbeen annotated with respect to MTU information. The request is sent tothe annotated patent database 268 for a record to be created for theannotated patent or application. The MSBTP data gathering section 72 mayfurther generate a patent term database entry request for a new patentterm found in the patent or application. This request is sent to thepatent term database 266 for a record to be created for the new patentterm.

As another example, when the document is related to marketing, sales,business (financial, market, economy, etc.), and/or technology, theMSBTP data gathering section 72 generates an MSBT database entry requestfor the document. The request is sent to the MSBT database 262 for arecord to be created for the MSBT document.

From the ingested documents, the MSBTP data gathering section 72classifies the documents with an MTU classification, which include anMTU name, undecided, and undecided/potential new MTU. The MSBTP datagathering section 72 adds the MTU classification to the database recordfor the document. The MSBTP data gathering section 72 routinely reviewsthe MTU classification of stored documents to determine if an MTUclassification update is needed. If so, the MSBTP data gathering section72 updates a document's MTU classification.

The MSBTP data gathering section 72 also processes stored documents withthe MTU classification of undecided/potential new MTU to determinewhether a new MTU should be created. If so, the MSBTP data gatheringsection 72 generates an MTU database entry request for the new MTU andsends it to the MTU database 264.

The data processing section 76 receives a selection of an MTU from thesubscription based user interface section 78 and a selection of areport, or reports, to be generated. The reports of the data processingsection 76 are per selected MTU(s) and include an existing patentlandscape report, a competitor existing patent analysis report, a “howwell the MTU is patent protected with existing patents” report, a marketimpact of the MTU in light of existing patents report, a value of an MTUin light of existing patents report, a forecasted future patentlandscape report, a competitor forecasted future patent analysis report,a “how well the MTU is patent protected with forecasted future patents”report, a market impact of the MTU in light of forecasted future patentsreport, a value of an MTU in light of forecasted future patents report,an architectural plan for developing a patent portfolio for an MTUreport, an expense & growth report for an MTU being developed per thearchitectural plan, a patent protection tracking report, a patent usereport, and a constructive notice report.

For a selected MTU, the data processing section 76, if not already done,expands the innovation of the MTU and expands the market opportunity forthe MTU and the expansion of the MTU. Expanding innovation of the MTUincludes identifying new unique values propositions for the MTU,identifying new features for the MTU, identifying new technicalchallenges for the MTU, identifying new uses for the MTU, and so on.Expanding the market opportunities includes identifying new marketopportunities for the expanded MTU and further includes identifyingother MTUs that have similar unique value propositions, similarfeatures, and/or similar technical challenges and determining the MTUapplicability in markets of the other MTUs.

From the selected MTU, the expansion of the MTU, and the expansion ofthe market opportunities, the data processing section 76 analyzes theMTU from an existing patent standpoint to produce one or more of theabove mentioned existing patent reports and/or analyzes the MTU from aforecasted future patent standpoint to produce one or more of the abovementioned forecasted future patent reports.

From the existing patent analysis, forecasted future patent analysis,and inputted data regarding patent position and/or patent spend, thedata processing section 76 generates an architectural plan for patentprotecting the MTU. The data processing section tracks execution of thearchitectural plan via a private database (one for each authorizeduser). To ensure quality of executing the architectural plan, the dataprocessing section includes an ML and/or AI patent applicationpreparation program and an ML and/or AI patent application prosecutionprogram.

From the stored data and the various other analysis performed by, and/orreports generated by, the data processing section, it generates one ormore reports regarding market exploitation of the patent protected MTU.For example, the data processing section 76 generates a report on usesof the patents of the MTU. As another example, the data processingsection generates a constructive notice report.

The co-processors of the improved computer 70 may be implemented in avariety of ways. For example, a co-processor is one or more computingentities and/or one or more computing devices. As another example, aco-processor is a dedicating processing module of a computing entityand/or of a computing device. As yet another example, a co-processor isa computing core of a computing device. As a further example, aco-processor is an allocation portion of processing resources of acomputing entity and/or of a computing device. As yet a further example,a co-processor is a temporary allocation of processing resources of auser computing device.

The various programs, including ML and/or AI programs, of the improvedcomputer for technology may be allocated to co-processors in a varietyof ways. For example, a co-processor is allocated multiple programs forexecution. As another example, a co-processor is dedicated to a specificprogram, or programs. As yet another example, co-processors areallocated programs on an as-needed basis. As a further example, eachprogram, or set of programs, is allocated to a dedicated set ofco-processors to increase parallel operations of the improved computer,the number of co-processors in a dedicated set can vary to accommodatescaling of parallel operations.

FIG. 25 is a schematic block diagram of a further embodiment of animproved computer for technology 70, which includes the MSBTP datagathering section 72, the data processing section 76, the subscriptionbased user interface section 78, the database interface unit 260, andthe system databases 74. The system databases 74 include the MSBT(marketing, sales, business, technology) database 262, the market-techunit (MTU) database 264, the patent terms database 266, the annotatedpatent database 268, a patent use database 270, a patent procurementdatabased 272, and a market impact database 278.

The MSBTP data gathering section 72 ingests a variety of documents. Asan example of documents, which far from an exhaustive list, thedocuments include articles from various publications, reports, financialdocuments, marketing material, sales material, technology documents,business documents, market documents, patent procurement documents,patent use documents, patent value documents, and patents. In general,the MSBTP data gathering section 72 seeks to ingest and process anydocument that pertains to a technology category, business regarding atechnology, financial reports and/or analysis of a technology and/orbusiness regarding technology, market reports and/or analysis of atechnology and/or business regarding technology, technical descriptionof a technology, and/or existing and/or projected use of a technology.

FIG. 26 is a schematic block diagram of a further embodiment of animproved computer for technology 70 that includes, in part, the MSBTPdata gathering section 72 and the system databases. The MSBTP datagathering section 72 includes an MSBT ingest and MTU classify unit 280,an MTU identify, create, and data populate unit 282, an MTU catalog unit284, an MTU correlation unit 286, a market impact unit 288, a patentterm recognition unit 290, a patent annotating unit 292, a patent useunit 294, and a patent procurement unit 296. As used herein, a unit isimplemented via one or more co-processors and/or one more processingmodules.

The MSBT ingest and MTU classify unit 280 ingests MSBT (marketing,sales, business, and technology) documents that include, but is notlimited to, financial data, business data, marketing data, sales data,technology data, and market data. The unit 280 processes each documentwith respect to MTU information (e.g., information relevant to an MTUrecord) and classifies documents with an MTU classification inconjunction with the MTU correlation unit 286. The unit 280 also createsMSBT database entry requests for documents to be saved as MSBT recordsin the MSBT database 262.

The MTU identify, create, and data populate unit 282 retrieves MSBTrecords from the MSBT database 262, annotated patent records from theannotated patent database 268, and/or patent term records from thepatent term database 266, and MTU records from the MTU database 264. Theunit 282 processes the MSBT records, the annotated patent records,and/or the patent term records to identify new data to add to anexisting MTU record and/or to identify edits to be made to existing MTUrecords. For new data to add to an existing MTU record, the unit 282generates a data populate request for the existing MTU record regardingthe new data and sends it to the MTU database 264. For data edits, theunit 282 generates a data populate request for the existing MTU recordregarding the data edits and sends it to the MTU database 264.

The MTU identify, create, and data populate unit 282 retrieves MSBTrecords, annotated patent records, and/or patent term records from therespective databases that have an MTU classification ofundecided/potential new MTU. The unit 282 processes the records todetermine if there is sufficient data to support the existence of a newMTU. If yes, the unit 282 generates a new MTU record request for the newMTU and sends it to the MTU database 264. The unit 282 also updates theMTU classification of the records from undecided/potential new MTU tothe name of the new MTU.

If there is not sufficient data to support the determination of a newMTU, the unit 282 determines whether the accumulated data is indicatingan increase or decrease in the likelihood of it representing a new MTU.When the data indicates a decrease in the likelihood of new MTU, theunit 282 determines whether the likelihood of a new MTU has droppedbelow a lower limit threshold (e.g., less than a 1% to 5% chance a newMTU is emerging). If yes, the unit 282 changes the MTU classification ofthe retrieved records from undecided/potential new MTU to undecided.

The MTU identify, create, and data populate unit 282 also retrieves MSBTrecords, annotated patent records, and/or patent term records from therespective databases that have an MTU classification of undecided. Theunit 282 processes the records to determine if there is sufficient datato support the existence of a potential new MTU. If yes, the unit 282updates the MTU classification of the records from undecided toundecided/potential new MTU.

The MTU catalog unit 284 retrieves MTU records from the MTU database tocatalog the records. In this context, cataloging means creating and/orupdating technology maps of MTUs by linking MTUs together in afunctional and/or hierarchical manner. A technology map is for aparticular technology category (e.g., communications technology,information technology, electrical technology, medical technology, etc.)or a combination of technologies (e.g., communications technology,information technology, and electrical technology) from a high-leveldown to a microscopic technical detail (e.g., fundamental components,circuits, and/or elements). MTU inclusion diagrams and MTU compositiondiagrams are derived from the technology maps.

The MTU correlation unit 286 is operable to ensure that MSBT records,annotated patent records, and/or patent term records are correlated withthe appropriate MTUs. In particular, the MTU correlation unit 286ensures that MTU classification of records is accurate and is drawn fromvalue MTU records.

The market impact unit 288 retrieves MSBT records and MTU records fromrespective databases to determine existing market impact of an MTU andto determine a forecasted future market impact of the MTU. For an MTU,the unit 288 generates a market impact record regarding the existingmarket impact of the MTU and/or the forecasted future market impact ofthe MTU.

The patent term recognition unit 290 ingests new patents (issued andpending), retrieves annotated patent records, and retrieves patent termrecords to identify new patent terms and/or to update existing patentterms in light of MTU classifications based on the ingested new patents.As used herein, a patent term is a claim term or a technical term. Aclaim term includes one or more words regarding a claim noun (e.g., anelement, a step, an input, output, and/or some quantifiable thing), aclaim descriptor (e.g., a feature, a function, a description, aninteraction, an operational limitation of a claim noun and/or the like),and/or a claim relator (relationship of two or more claim nouns). Atechnical term includes one or more words that is regarding a technicalaspect of an MTU.

The patent term recognition unit 290 identifies new patent terms in theingested patents based on the retrieved patent term records and/or theretrieved annotated patent records. The unit 290 determines whichrecords to retrieve based on one or more of a multitude of factors,which includes assignee name, inventor name, patent title, patentclassification, and/or similar patent terms. For a new patent term, theunit 290 generates a new patent term record request and sends it to thepatent term database 266. For updating an existing patent term, the unit290 generates an update patent term record request and sends it to thepatent term database 266.

The patent annotating unit 292 ingests new patents (issued and pending),retrieves annotated patent records, and retrieves patent term records toannotate the ingested patents in light of MTU data. As used herein,annotate means highlighting patent terms within a patent, identifyinggeneral patent information, identifying foreign counterparts, extractingtechnology boundary data that pertain to technical boundaries of anexisting MTU and/or a potential new MTU, generating an MTU orientatedgeneral description of the patent, identifying a science category,identifying product and/or service data, identifying manufacturing data,and/or identifying market impact data.

For a new annotated patent, the patent annotating unit 292 generates anew annotated patent record request and sends it to the annotated patentdatabase 268. The unit 292 also routinely reviews existing annotatedpatent records to determine, based on more recent ingested data, whetheran existing annotated patent record should be updated. If so, unit 292generates an update an existing annotated patent record request andsends it to the annotated patent database 268.

The patent use unit 294 ingests documents regarding patent use (e.g.,patent sales, patent litigation, patent licensing, product/serviceinformation, technology investments, assignment records, etc.) andretrieves existing patent use documents from the patent use database270. For new documents, unit 294 generates a new patent use recordrequest and sends it to the patent use database 270. The unit 294 alsoroutinely reviews existing patent use records to determine, based onmore recent ingested data, whether an existing patent use record shouldbe updated. If so, unit 294 generates an update an existing patent userecord request and sends it to the patent use database 270.

The patent procurement unit 296 ingests and processes documentsregarding pricing of various patent services and/or patent filingstatistics, patent prosecution statistics, patent issuance statistics,and patent abandonment statistic. For new documents, unit 296 generatesa new patent procurement record request and sends it to the patentprocurement database 272. The unit 296 also routinely reviews existingpatent procurement records to determine, based on more recent ingesteddata, whether an existing patent procurement record should be updated.If so, unit 296 generates an update an existing patent procurementrecord request and sends it to the patent procurement database 272.

By quantifying technology with market-tech units, which have definabletechnical boundaries, the improved computer has significantly greaterdata consistency with respect to most, if not all, of the functions itoffers in comparison to services that support the conventional patentprocess. The greater data consistency of MTUs enables more efficient andeffective prior art searching, better architectural planning of patentprotecting a technology, clear definitions for technology, bettervaluation of technology, and/or any other benefits of better dataconsistency.

FIG. 27 is a schematic block diagram of a further embodiment of animproved computer for technology 70 that includes the system databases262-274, the database interface unit 260, the subscription based userinterface section 78, and the data processing section 76. The dataprocessing section 76 includes a TMPIV (Technology, Market impact,Patent protection, Innovation, and Value of technology) development unit250, an existing TMPIV analysis unit 246, a future TMPIV forecastingunit 248, a patent preparation unit 254-1, a patent prosecution unit254-2, a patent use unit 256-1, and constructive notice unit 256-2.

The existing TMPIV analysis unit 246 generates one or more reports 82based on data retrieved from the MTU database 264, from the MSBTdatabase 262, from the annotated patent database 268, the from thepatent term database 266, and/or from the market impact databased 274.For example, the unit 246 generates an existing patent landscape reportfor an MTU based on per MTU existing patent data 310 (annotated patentsand/or patent terms), per MTU existing MSBT data 312, and per MTU marketimpact data 314 for the selected MTU.

The unit 246 generates an existing patent landscape report for aselected MTU to include a list of inventions that have some form ofpatent protection, a list of assignees of existing patents (issued andpending), a breakdown of existing patents per assignee, a number oftotal inventions that should exist to date for the technology, an idealnumber of inventions that should have been patent protected to date, ageneral description of the MTU, general descriptions of the existingpatents, a comparison of existing patents to the total number ofinventions to date, and/or a comparison of existing patents to an idealnumber of inventions that have been patent protected to date.

The unit 246 generates a competitor existing patent analysis reportregarding an MTU based on the existing patent landscape report tailoredfor a particular assignee. The report further compares the particularassignee's patenting of the MTU to date with the patenting to date ofthe MTU by other assignees.

The unit 246 generates a “how well the MTU is patent protected withexisting patents” report based on the existing patent landscape reportand the retrieved data. The report includes the list of inventions thathave some form of patent protection, the number of total inventions thatshould exist to date for the technology, the ideal number of inventionsthat should have been patent protected to date, a quality analysis ofthe existing patent protection, and a calculation of the level of patentprotection based on a ratio of the actual number of inventionsprotection with respect to the ideal number of inventions and thequality of the existing patent protection. The quality includes acumulative score of per patent application preparation and prosecutionquality score and a patent portfolio sufficiency score (e.g., balance,breadth, scope, etc.).

The unit 246 generates a market impact of the MTU in light of existingpatents report based on the existing patent landscape report and theretrieved data. The report includes existing total available market(TAM) data, a compound annual growth rate (CAGR) for the TAM, serviceobtainable market (SOM) data, a CAGR for the SOM, influence of themarketable features of the MTU on the TAM and/or the SOM, influence ofthe unique value propositions (UVPs) of the MTU on the TAM and/or theSOM, influence of the technical challenges of the MTU on the TAM and/orthe SOM, and a market impact calculation on the TAM and/or on the SOM.

The unit 246 generates a value of an MTU in light of existing patentsreport based on the how well patented report, the market impact report,and a market-patent “k” factor. The report includes the relevant datapoints of the other reports and a calculation of the value of the MTU atpresent. The calculation could further include past values of the MTU.

The future TMPIV forecasting unit 248 generates one or more reports 84based on data retrieved from the MTU database 264, from the MSBTdatabase 262, from the annotated patent database 268, from the patentterm database 266, and/or from the market impact databased 274. Forexample, the unit 248 generates a forecasted future patent landscapereport for an MTU based on per MTU future patent data 316, per MTUfuture MSBT data 318, and per MTU future market impact data 320 for theselected MTU.

The unit 248 generates a forecasted future patent landscape report for aselected MTU to a number of total inventions that should be created frompresent day to end of life of the MTU, an ideal number of inventions tobe patent protected from present day to end of life of the MTU, ageneral description of the MTU, a forecast of assignees of futurepatents, and/or a list of technical challenges, unique valuepropositions, and/or marketable features for future inventions.

The unit 248 generates a competitor forecasted future patent analysisreport based on the future patent landscape report tailored for aparticular assignee. The report further compares the particularassignee's forecasted future patenting of the MTU with the forecastedfuture patenting of the MTU by other assignees.

The unit 248 generates a “how well the MTU is patent protected withforecasted future patents” report based on the future patent landscapereport and the retrieved future forecasting data. The report includesthe number of total inventions that should be created from present dayto end of life of the MTU, the ideal number of inventions that should bepatent protected from present day to end of file, a quality projectionof the future patent protection, and a calculation of the level ofpatent protection based on desired patent position, a ratio of thenumber of inventions that will likely be patent protected based ondesired patent position with respect to the ideal number of inventionsand the quality of the future patent protection. The quality includes acumulative score of per patent application preparation and prosecutionquality forecasted score and a patent portfolio sufficiency forecastedscore (e.g., balance, breadth, scope, etc.).

The unit 248 generates a market impact of the MTU in light of forecastedfuture patents report based on the future patent landscape report andthe retrieved future forecasting data. The report includes, on ayear-by-year basis, forecasted total available (or addressable) market(TAM) data, a forecasted compound annual growth rate (CAGR) for the TAM,forecasted service obtainable market (SOM) data, a forecasted CAGR forthe SOM, forecasted influence of the marketable features of the MTU onthe TAM and/or the SOM, forecasted influence of the unique valuepropositions (UVPs) of the MTU on the TAM and/or the SOM, forecastedinfluence of the technical challenges of the MTU on the TAM and/or theSOM, and a forecasted market impact calculation on the TAM and/or on theSOM.

The unit 248 generates a value of an MTU in light of forecasted futurepatents report based on the forecasted how well patented report, theforecasted market impact report, and the market-patent “k” factor. Thereport includes, on a year-by-year basis, the relevant data points ofthe other reports and a calculation of the future value of the MTU.

The TMPIV development unit 250 generates a development report 86 thatincludes an architectural plan for developing a patent portfolio for anMTU report, an expense & growth report for the MTU based on thearchitectural plan, and a patent protection tracking report. The unit250 generates its reports 86 based on the financial input 306, thepatent position input 308, and/or the reports 82 and 84 produced by theexisting TMPIV analysis unit 246 and the future TMPIV analysis unit 248.Note that the subscription based user interface section 78 receivesfinancial input data 306 and/or patent position input data 308 for anMTU from an authenticated user device (e.g., a computing device or acomputing entity).

The patent preparation unit 254-1 generates a patent application, or atleast a claim set, for an invention of an MTU in accordance witharchitectural plan and MTU technical data 322. The MTU technical data322 includes data regarding the MTU from the MTU database 264, businessand technical information regarding the MTU from the MSBT database 262,market impact data from the market impact database 274, annotatedpatents from the annotated patent database 268, and/or patent terms fromthe patent terms database 266.

The patent prosecution unit 254-2 generates a prosecution response(e.g., an office action response) for a pending patent applicationregarding an invention of an MTU in accordance with architectural planand MTU technical data 322. The MTU technical data 322 includes dataregarding the MTU from the MTU database 264, business and technicalinformation regarding the MTU from the MSBT database 262, market impactdata from the market impact database 274, annotated patents from theannotated patent database 268, and/or patent terms from the patent termsdatabase 266.

FIG. 28 is a schematic block diagram of a further embodiment of animproved computer for technology 70. In this embodiment, the improvedcomputer includes the MSBTP (marketing, sales, business, technology,patents) data gathering section 72, the system databases 74, thesubscription based user interface 78, the existing TMPIV (Technology,Market impact, Patent protection, Innovation, and Valuation) analysisunit 246, the future TMPIV analysis unit 248, the TMPIV portfoliodevelopment unit 250. The patent application preparation and prosecutionunit 254, and the patent exploitation unit 256. Units 246-256 are partof the data processing section 76.

The system databases 74 stores MSBT data, patent data, patent terms,market-tech units (MTU) data, patent use data, market impact data, andpatent procurement data. In an embodiment, the data of the systemdatabases 74 is not directly accessible to authorized and authenticateduser devices. Such user devices have read access only to the data of thesystem databases 74 indirectly via the data processing section 76.

The units of the data processing section 76 have read access to the dataof the system databases 74, but do not have write access. The reportsgenerated by the various units are stored by the respective units. Therespective units may further store the data used to generate thereports. Authorized and authenticated user devices have read access onlythe reports and do not have read or write access to the data used togenerate the reports, if stored by a respective unit.

The existing TMPIV analysis unit 246 includes a technology-patentmaturity unit 340, an existing patent landscape unit 342, a competitorexisting patent analysis unit 344, an existing “how well protected” unit346, an existing market impact unit 348, and an MTU valuation in lightof existing patents unit 350. The technology-patent maturity unit 340determines the generation of an MTU and the phase of the currentgeneration. The unit 340 also calculates the total number of inventionsthat are likely to be created over the life of the MTU, the percentageof the total number of inventions that should have been invented to date(e.g., existing inventions) and the remaining number of inventions to beinvented (e.g., forecasted future inventions).

The existing patent landscape unit 342 generates an existing patentlandscape report as generally discussed with reference to FIG. 27 and asdescribed in greater detail with reference to subsequent figures. Thecompetitor existing patent analysis unit 344 generates a competitorexisting patent report as generally discussed with reference to FIG. 27and as described in greater detail with reference to subsequent figures.

The existing “how well protected” unit 346 generates an existing “howwell protected” report as generally discussed with reference to FIG. 27and as described in greater detail with reference to subsequent figures.The existing market impact unit 348 generates an existing market impactreport as generally discussed with reference to FIG. 27 and as describedin greater detail with reference to subsequent figures. The MTUvaluation in light of existing patents unit 350 generates an existingMTU valuation report as generally discussed with reference to FIG. 27and as described in greater detail with reference to subsequent figures.

The future TMPIV analysis unit 248 includes the technology-patentmaturity unit 340, a forecasted future patent landscape unit 352, acompetitor forecasted future patent analysis unit 354, a forecastedfuture “how well protected” unit 356, a forecasted future market impactunit 358, and an MTU valuation in light of forecasted future patentsunit 360.

The forecasted future patent landscape unit 352 generates a forecastedfuture patent landscape report as generally discussed with reference toFIG. 27 and as described in greater detail with reference to subsequentfigures. The competitor forecasted future patent analysis unit 354generates a competitor forecasted future patent report as generallydiscussed with reference to FIG. 27 and as described in greater detailwith reference to subsequent figures.

The forecasted future “how well protected” unit 356 generates aforecasted future “how well protected” report as generally discussedwith reference to FIG. 27 and as described in greater detail withreference to subsequent figures. The forecasted future market impactunit 358 generates a forecasted future market impact report as generallydiscussed with reference to FIG. 27 and as described in greater detailwith reference to subsequent figures. The MTU valuation in light offorecasted future patents unit 360 generates a forecasted future MTUvaluation report as generally discussed with reference to FIG. 27 and asdescribed in greater detail with reference to subsequent figures.

The TMPIV portfolio development unit 250 includes a patent planning unit362, an expense and growth unit 364, private patent tracking databases366, and a patent plan execution tracking unit 368. The patent planningunit 362 generates the architectural plan for patent protection of anMTU as generally discussed with reference to FIG. 27 and as described ingreater detail with reference to subsequent figures. The expense andgrowth unit 364 calculates the expense of patenting inventions per thearchitectural plan, calculates prosecution timing and expense of pendingpatent applications, calculates timing and expense of issuing patentapplications, and calculates timing and expense of subsequent filings.

The private patent tracking databases 366 are individual databases forauthorized and authenticated user devices that are affiliated withexecuting an architectural plan for an MTU. Note that a private database366 tracks one or more MTU architectural plans of a user (via itsdevice). The patent plan execution unit 368 coordinates data entry inthe private databases 366 and generates periodic (and/or on-demand)reports regarding the execution of the architectural plan.

The patent preparation and prosecution unit 254 includes an MTUtechnology for lawyers unit 370, an invention identification (ID) andclaim drafting unit 372, a patent application drafting unit 374, apatent prosecution unit 376, and a patent quality analysis unit 378. TheMTU technology for lawyers unit 370 provides general descriptions ofrelevant MTUs that are associated with an MTU of which an invention isbeing patented. For example, if the invention is regarding a touchscreen controller, the MTU technology for lawyers unit 370 retrievesgeneral descriptions of touch screen controllers, touch screens, and thedevices using touch screens (inclusion MTUs-higher tier MTUs). The MTUtechnology for lawyers unit 370 may further retrieve generaldescriptions of touch screen controller composition MTUs (lower tierMTUs).

The invention identification (ID) and claim drafting unit 372 generatesa report that identifies novel aspects of an invention of an MTU basedon the technical boundaries of the MTU and a particular problem theinvention is addressing. In an embodiment, the unit 372 uses aninteractive ML and/or AI program to generate an initial report regardingnovel aspect and a series of questions to tune the novel aspects andoutline independent claims.

The patent quality analysis unit 378 generates a report regarding patentquality by reviewing and analyzing the claims, support of the claims,clarity of the invention being patented, clarity of problem beingsolved, clarity of benefit of invention, and/or relative scope of claimcoverage. The determination of patent quality will be discussed ingreater detail with reference to subsequent figures.

The improved computer disclosed herein provides an improved computerarchitecture, provides many new technologies, and provides manysignificant technical improvements and/or technical advantages overexisting computers and computer programs that support the conventionalpatent process. These include, but are not limited to, one or more of:

-   -   increased data consistency regarding data identification, data        retrieval, data analysis, and/or data results through the use of        one or more new computer co-processing units and/or functions        that quantify technology in terms of market-tech units (MTUs);    -   one or more new computer co-processing units and/or functions to        identify new MTUs and create database records for new MTUs, one        or more new computer co-processing units and/or functions to        identify documents relevant to new and/or existing MTUs, to        retrieve such documents, dissecting such documents to extract        relevant MTU data, create database records for storing such        documents, and/or to update existing MTU records with further        MTU data, which further improves data consistency;    -   one or more new computer co-processing units and/or functions to        generate an architectural plan to patent protect an MTU over the        life of the MTU, only patents that service a purpose per the        plan are pursued, which eliminates waste and increases        effectiveness;        -   to answer the question of “how many patents are needed to            appropriately protect a technology?′        -   to calculate, for the quantified technology as represented            by an MTU, a total number of inventions likely to be            invented over the life of the quantified technology;        -   to calculate the life of a quantified technology (MTU);        -   to generate a report regarding invention types for the MTU            and to calculate quantities for each invention type;    -   one or more new computer co-processing units and/or functions to        calculate, on a year-by-year basis (or other frequency) expense        and growth of patent protection of an MTU from its infancy to        its end of life;    -   one or more new computer co-processing units and/or functions to        calculate a year-by-year (or other frequency) value of an MTU        from its infancy to its end of life;    -   one or more new computer co-processing units and/or functions to        generate an existing patent landscape report (and/or prior art        search report) for an MTU (and/or MTUs);    -   one or more new computer co-processing units and/or functions to        track and record execution of an architectural plan for patent        protecting an MTU; and/or    -   one or more new computer co-processing units and/or functions to        generate an improved and streamlined architectural plan to        patent protect an MTU over the life of the MTU, which;        -   answers the question of “how many patents are needed to            appropriately protect a technology?”        -   calculates, for the quantified technology as represented by            an MTU, a total number of inventions likely to be invented            over the life of the quantified technology;        -   calculates the life of a quantified technology (MTU); and/or        -   generates a report regarding invention types for the MTU and            to calculate quantities for each invention type.

Like other computers, the improved computer operates at the machinelevel where data is represented as unique sequences of 1's and 0's. Forthe improved computer data is one of data operands, operationalinstructions, or resulting data, where a set of operational instructions(or operational codes, or op codes) is performed on one or more dataoperands to produce resulting data. Within the improved computer it iscommon for the resulting data of a previously executed set ofoperational instructions to be a data operand(s) [intermediate operand]for a subsequently executed set of operational instructions, where a setincludes one or more operational instructions.

Operational instructions are programming language specific and providethe instructions for the computer to read data operands, write dataoperands, write data results, and/or perform a function on a dataoperand(s). Examples of functions includes, but are not limited to, add,subtract, shift left, shift right, multiply, divide, a logic AND, alogic OR, a logic XOR, etc. A generic format for an operationalinstruction is [function; address for operand; (additional address foradditional operands if functions involve two or more operands); addressof where to write the data result].

The data operands, operational instructions, and data results are storedwithin the improved computer's memory as unique sequences of 1's and0's. How the 1's and 0's are stored, retrieved, and processed within thecomputer dictate whether they are related to a data operand, anoperational instruction, or a data result. All of the unique sequencesof 1's and 0's regarding a program need to be properly associated withdata operands, operational instructions, and data result; and need to beretrieved, processed, and/or stored in a precise manner for the programto operating correctly (e.g., produce the desired data result(s) fromone or more initial data operands and/or one or more intermediate dataoperands).

A new combination and/or ordering of operational instructions that isexecuted by the improved computer on data operands (new, known, initial,and/or intermediate) to produce a new data result is novel. Thecreation, storage, and/or execution of operational instructions by animproved computer on data operands to produce a new data result are, init of themselves, technical challenges.

Creating a new tool via the novel programming of a computer provides thebenefits of any physical tool, which include, but are not limited to,improving performance, efficiency, accurately, reliability, safety,resolution, etc. of an existing task, providing new solutions to anexisting task, and providing solutions to new tasks.

The human meaning of the 1's and 0's of the data operands, theoperational instructions, and/or the data results does not change thetechnical challenges of programming a computer to produce an output, oroutputs, through one or more sets of operational instructions operatingon initial data operands and/or intermediate operands.

FIG. 29 is a flow diagram of another example of a generating a patentprotection plan for a technology (one or more market-tech units [MTUs)].This diagram focuses on the improved computer for technology answeringthe questions of (a) How many patents are needed? (b) What will it cost?and (c) What is the return? These questions cannot be reliably andconsistently answered without first quantifying a piece of technology(e.g., establish technology boundaries that are definitive andrepeatably identifiable).

When a piece of technology has been quantified into an MTU, the questionof “how many patents are needed” can be answered. The answer depends ona plurality of data (inputted and calculated). The inputted dataincludes desired patent position and desired patent spend. Thecalculated data includes a level of disruption of the MTU (e.g.,incremental, better mouse trap, evolutionary, revolutionary), level ofinnovation (e.g., driven by quantity and/or complexity of uniquevaluation propositions, of marketable features, and/or of technicalchallenges), the total number of inventions likely to be invented overthe life of the technology, generation and phase data for the MTU,previous generation (PG) and/or current generation (CG) existingpatents, overall life and remaining life of MTU, and the patentlandscape for the MTU (existing and forecasted future).

From these inputs, the improved computer calculates a number ofinventions to patent protection on a year-by-year basis. This includes abreakdown of invention types per technical challenge, UVP, and/ormarketable feature. It further includes how and where patent protectionis to be sought.

When an initial year-by-year number inventions to patent protect hasbeen determined, the question of “what will it cost” can be answered.The expense & growth unit 364 answers the question by determiningyear-by-year expense and portfolio growth numbers based on theyear-by-year number of inventions to patent protect. If the projectedcosts exceed the desired patent spend, then the improved computerrequests the user device to adjust the patent position and/or the patentspend.

Once the year-by-year number of inventions to patent protection andcosts have been determined, the question of “what is the return” can beanswered. The value units 350 & 360 calculate a year-by-year value ofthe MTU based on market impact data, how well patent protected, and the“k” factor. The year-by-year ROI is calculated based on the year-by-yearvalue and the year-by-year expenses.

FIG. 30 is a schematic block diagram of a further embodiment of animproved computer for technology. In this embodiment, some of the unitsof the data processing section 76 are shown, which are the tech-patentmaturity unit 340, the existing patent landscape unit 342, the existing“how well protected” units 346, the existing market impact unit 348, theexisting value unit 350, the forecasted patent landscape unit 352, theforecasted “how well protected” unit 356, the forecasted market impactunit 358, the forecasted MTU value unit 360, the patent planning unit362, the expense and growth unit 364, an aggregate unit 365, and anadjust unit 367.

The tech-patent maturity unit 340 generates generational (GEN) data 390for an MTU. The GEN data includes the generations of an MTU (previous,current, and/or next) and the phases of each generation. The GEN data390 further includes the life span of each generation and the time frameof each phase.

The units 342-350 use the GEN data 390, the MSBT data 392, the marketimpact data 394, and the MTU patent data 396 to generate an MTU existingvalue report 398. The units 352-360 use the GEN data 390, the MSBT data392, the market impact data 394, and the MTU patent data 396 to generatean MTU future value report 400.

For an MTU, the patent planning unit 362 generates a year-by-year MTParchitectural patent protection plan 402 based the forecasted patentlandscape report for the MTU produced by the forecasted patent landscapeunit 352, the MTU existing value report 398, the forecasted future valuereport 400, and on the patent position input 308. For the MTU, theexpense and growth unit 364 generates a year-by-year expense and growthreport 404 based on the MTU patent plan 402. The expense and growth unit364 may adjust the year-by-year expense and growth report 404 based onthe financial input 306, which includes a desired patent spend.

For each additional MTU, the patent planning unit 362 generates a uniqueyear-by-year MTU patent plan 402 and the expense and growth unit 364generates a unique year-by-year expense and growth report 404.

The aggregate unit 365 aggregates patent plans 402 of individual MTUsinto an overall patent plan 406, which covers multiple MTUs of interestto a user. The aggregate unit 365 also aggregates the expense and growthreports 404 of the individual MTUs into an overall expense and growthreport 408.

The adjust unit 367 compares the overall expense and growth report 408in light of the financial input 306. If the overall cost is too high,the adjust unit 367 adjusts, for one or more MTUs, the desired patentposition 410 and/or patent spend 412. This can be done on a year-by-yearbasis and an MTU-by-MTU basis to best balance spend and patent positionfor the MTUs.

FIG. 31 is a diagram of an example of a relative number of inventionsbeing created over the life of a technology (a market-tech unit [MTU)].A generational life of an MTU includes a create phase, a deploy phase,an optimize phase, a mature phase, and a decline phase. In the createphase, the MTU is being created and not yet commercialized. In thedeploy phase, an initial commercial embodiment of the MTU is madepublicly available. In the optimize phase, commercial embodiments of theMTU are optimized for performance, production costs, features, and/orother optimizations and revenue from the commercial embodimentsincreases. In the mature phase, the commercial embodiments of the MTUare optimized and revenue from the commercial embodiments increases at adecreasing rate. In the decline phase, revenue from the commercialembodiments of the MTU decreases at an increasing rate.

The creation of inventions occur over the life of the MTU. In general,the relative number of inventions is depicted by the line. Fundamentalinventions are typically created during the create phase and a portionof the deploy phase. Commercially necessary inventions are typicallycreated in part of the create phase, throughout the deploy phase andinto the optimize phase. Commercial expansion inventions are typicallycreated in part of the deploy phase through the mature phase and intothe decline phase.

FIG. 32 is a diagram of an example of a relative invention breadth ofinventions being created over the life of a technology (a market-techunit [MTU)]. In general, fundamental inventions have more breadth thancommercially necessary inventions, which have more breadth thancommercial expansion inventions.

FIG. 33 is a diagram of an example of a relative total number ofinventions, a relative ideal number of inventions over the life of atechnology (a market-tech unit [MTU)], and existing inventions protectedto date. The blue line represents the calculated total number ofinventions that are likely to be created over the life of the MTU. Thered line represents the calculated ideal number of inventions that arelikely to be patent protected. The black line represents the inventionsthat have been patent protected to date (e.g., existing inventions withpatent protection).

The improved computer calculates the data of FIGS. 31-33 and it's usedby the various units of the improved computer. For example, the patentplanning unit 362 uses the data as part of its function to generate anarchitectural plan for patent protecting an MTU.

FIG. 34 is a flow diagram of another example of a generating a patentprotection plan for multiple market-tech units [MTUs]. As discussed withthe reference to FIG. 30 , the adjust unit 367 generates a financialadjustment 412 and/or a patent position adjustment 410 for anarchitectural plan for one or more MTUs.

In this example, the architectural plan, the corresponding expense, thecorresponding value, and the corresponding ROI are created for two MTUson a year-by-year basis. After the aggregate unit 365 combined the tworeports, the adjust unit 367 adjusted the patent position and cost forMTU #2 in year 1 and adjusted the patent position and cost for MTU #1 inyear 2. The other years remain as originally calculated.

FIG. 35 is a logic diagram of an example of a method for generating apatent protection plan regarding a technology (a market-tech unit[MTU)]. The method begins at step 420 where the improved computerreceives an input for a desired patent position (e.g., a sliding scalefrom weak to superior). The method continues at step 422 where theimproved computer determines whether the inputted patent position isobtainable.

To determine whether the desired patent position is obtainable, theimproved computer determines the total number of inventions andinvention types that are likely to be created over the life of the MTU,the ideal number of inventions and invention types to patent protectover the life of the MTU, the current phase, and the number ofinventions that have been patent protected to date (e.g., existingpatent protection). From this data, the improved computer determines thepatent positioned achieved to date (e.g., a comparison of the existingpatent protection with the ideal number of inventions that should havebeen patent protected to date).

If the achieved to date patent position is comparable to the inputteddesired patent position, then the desired patent position is obtainable.If the achieved to date patent position is less than the inputteddesired patent position, the improved computer determines whether asufficient number and type of inventions remain to be created (e.g.,future forecasted patent protection) to obtain the desired patentposition. If so, the desired patent position is obtainable. If not, thedesired patent position is not obtainable.

If the desired patent position is not obtainable, the method repeats atstep 420. If the desired patent position is obtainable, the methodcontinues at step 424 where the improved computer generates ayear-by-year multi-year architectural plan for patent protecting an MTU.The method continues at step 426 where the improved computer generates ayear-by-year cost report for the plan.

The method continues at step 428 where the improved computer compares,on a year-by-year basis, the calculated costs with a desired patentspend. The method continues at step 430 where the improved computerdetermines whether the calculated costs exceeds the desired patentspend. Typically, the comparison will prioritize the calculated costsand desired patent spend for the current year, then for the next year,and so on.

If the calculated costs exceed the desired spend, the method continuesat step 432 where the improved computer receives an input to decreasethe desired spend for a given year, or years, and/or to decrease thedesired patent position. Note that, to keep the cost of the current yearand the following year at desired patent spends, the inventionprotection rate in subsequent years can be increase so that the desiredpatent position can still likely be obtained. After step 432, the methodrepeats at step 424.

When the calculated costs are not too high (e.g., are comparable to thedesired patent spend), the method continues at step 434 where theimproved computer calculates the year-by-year value of the MTU. Themethod continues at step 436 where the improved computer compares thecalculated ROI (calculated value divided by calculated costs) with adesired ROI. The method continues at step 438 where the improvedcomputer determines whether the calculated value and/or the calculatedROI are too low. If yes, the method continues at step 440 where theimproved computer receives an input to change the patent spend, thedesired patent position, the desired value, and/or the desired ROI andthe method repeats at step 424.

When the calculated value and/or the calculated ROI are acceptable, themethod continues at step 442 where the improved computer generates areport that includes the multi-year architectural plan, the multi-yearcosts, the multi-year growth of patent protection, the multi-year valueof the MTU, and the multi-year ROI. Note that the improved computerroutinely performs this method to update, if needed, the report as moredata is ingested.

FIG. 36 is a diagram of an example of implementing a method forgenerating a patent protection plan regarding a technology (amarket-tech unit [MTU)]. In this example, a new product/service is beingdeveloped for a targeted market opportunity. The new product/serviceincludes a new tech block A, a new tech block B, and a new tech block C.This example new product is the same as used in the example of FIG. 11 .In this example, however, the improved computer generates a report forpatent protecting the new product/service in accordance with there-engineered patent process and the functions of the improved computer.

The high-level functions performed by the improved computer includesidentify MTUs, expand MTUs, expand market opportunities for MTUs,perform existing and future forecasted invention and patent analysis,value the MTUs, and generate a report that includes existing value ofMTUs, future value of MTUs, the forecasted costs of patent protectingthe MTUs, and an architectural plan to patent protect the MTUs.

To begin, the improved computer equates the new product to an MTU, thenew tech block A to an MTU, the new tech block B to an MTU, and the newtech block C to an MTU. An equated MTU may be an existing MTU or a newMTU. Note that the product and each of the tech blocks could includemultiple MTUs, but for simplicity of discussion, each only includes oneMTU.

With the MTUs identified, the improved computer attempts to expand theinnovation level of the MTUs. In general, the innovation focus of thenew product and its new tech blocks is initially targeted to producing acommercially viable product. The improved computer expands thefundamental, commercially necessary, and commercial expansion inventionsbeyond the commercially viable product to encompass how each MTUinfluences the markets of interests, which ties into the next step. Fromthe MTUs and expanded innovation of the MTUs, the improved computerexpands the market reach (e.g., market opportunities) for each MTUbeyond the targeted market opportunity.

The improved computer then performs an innovation and patent analysisfor each of the MTUs. This involves calculating the total number ofinventions that are likely to be created over the life of an MTU, theideal number of inventions to patent protect over the life of the MTU,the existing patent protection of inventions, and a future forecast ofpatent protection for inventions.

Next, the improved computer calculates the year-by-year value of each ofthe MTUs and then generates the report. As an example, the improvedcomputer calculated that the desired number of inventions to protect foreach of the MTUs is 15 for the product MTU, 12 for the tech block A MTU,9 for the tech block B, and 18 for the tech block C MTU. By patentprotecting this number of inventions and the corresponding inventiontypes, the desired patent position (e.g., superior) is obtained.

In comparison with the conventional patent process example of FIG. 11 ,1 invention was patent protected for the product while the improvedcomputer determined that 15 inventions of particular types should bepatent protected. In the conventional patent process example, 0inventions were patent protected for tech block A while the improvedcomputer determined that 12 inventions of particular types should bepatent protected.

In the conventional patent process example, 22 inventions were disclosedand 15 of them were patent protected for tech block B, while theimproved computer determined that 9 inventions of particular typesshould be patent protected. In the conventional patent process example,5 inventions were disclosed and 4 of them were patent protected for techblock C while the improved computer determined that 18 invention ofparticular types should be patent protected.

The under and over patenting of the product and its tech blocks of theconventional patent process would not be realized until a patent disputearose regarding the product and/or its tech blocks. With re-engineeredpatent process supported by the improved computer, the productmanufacturer has confidence from day 1 of developing the product and itstech blocks that, by following the report produced by improved computer,the manufacturer will have a superior patent position if a patentdispute arises regarding the product and/or its tech blocks.

FIG. 37 is a schematic block diagram of an example of a graphical userinterface (GUI) of an improved computer for technology for initiating anMTU query. The initial search window 450 includes a field for enteringan MTU name, a first set of buttons for selecting a physical sciencetechnology category, and a second set of buttons for selecting a lifescience technology category. The initial window 450 may further includesadditional sets of buttons for other technology categories and/or a setof buttons for various technology sub-categories. A button may include ageneral description via a right click on the button and/or a hover overthe button.

In another embodiment, the initial search window 450 includes one ormore of a field for a patent holder's name, a field for a product and/orservice name, a field for a unique value proposition, a field formarketable features, a field for technical challenges, and a field forproblems. A field may include a drop-down window for selecting from alist of relevant names.

FIG. 38A is a schematic block diagram of an example of auser-interactive graphical representation of a market-tech unit (MTU)data record 452 of the MTU database. In an embodiment, an MTU recordincludes an MTU name & catalog section, a data section, a technicaldiscussion section, and a diagram section. The MTU name & catalogsection includes fields for an MTU name, MTU inclusion information(higher tier MTUs), MTU composition information (lower tier MTUs), andan indication as to whether the MTU is a fundamental MTU. As usedherein, a field means an attribute of a database record that includesone or more sets of data values (where a set includes one or more datavalues and a data value includes digital data regarding text, audio,video, images, graphics and/or other digital content). A field mayfurther include storage characteristics of data values within the recordand/or within the database.

The data section of the MTU record 452 includes fields for a generaldescription of the MTU, metadata, related MTUs, MTU synonyms, sciencecategories, MTU boundaries, manufacturing data, market impact data, andMSBTP (marketing, sales, business, technical, and patent) data. The MTUboundaries field includes fields for unique values propositions of theMTU, marketable features of the MTU, technical challenges of the MTU,problems to inventive embodiments information, and standardsinformation. The MSBTP data section includes fields for marketing data,advertising data, financial data, business data, market data, technologydata, patent data, and product/service data.

The diagram section includes fields for one or more MTU inclusionfunctional diagrams, one or more MTU inclusion hierarchy diagrams, oneor more MTU composition functional diagrams, one or more MTU compositionhierarchy diagrams, and one or more MTU composite diagrams. Theinclusion diagrams include the MTU and higher tier MTUs. The compositiondiagrams include the MTU and lower tier MTUs. The composite diagramsinclude multiple higher tiers of MTUs and/or multiple lower tiers ofMTUs.

Each diagram uses symbols (e.g., electrical symbols, graphic images,labeled box, etc.) to represent MTUs. The MTUs are coupled togetherbased on MTU interaction between them. The interaction is labeled inaccordance with the technology category. For example, MTU interactionfor electrical technology diagrams are labeled with, as a non-exhaustiveexample list, signal type, signal flow, signal level, current, voltage,power, signal manipulation, etc. As another example, MTU interaction forcommunication technology diagrams are labeled with, as a non-exhaustiveexample list, audio in, audio out, video in, video out, analog signal,digital signal, etc. As a further example, MTU interaction for chemicaltechnology diagrams are labeled with, as a non-exhaustive example list,combustion reaction, electrical reaction, decomposition reaction,neutralization reaction, precipitation reaction, synthesis, etc.

The technical discussion section includes fields for MTU inclusiontechnical discussion and MTU composition technical discussion. Eachtechnical discussion is written in a manner for a person of averageskill in the art to understand the use concepts of the MTU within thetechnical environment(s) in which it resides (i.e., a discussion of theMTU inclusion functional diagram) and to understand the operationalconcepts of the MTU based on the MTUs it includes (i.e., a discussion ofthe MTU composition functional diagram). Note that the various sectionsof the MTU record 452 will be described in greater detail with referenceto subsequent Figures.

In an embodiment, the improved computer generates one or more MTUrecords for an MTU based on inclusion MTUs. For example, multiple MTUrecords are generated for an MTU which has more than one MTU inclusionpath. For example, a touch screen is used in portable computing devicessuch as cell phones, tablets, smart phones, laptops, and two-way radios.In this example, five MTU records would be created, one for an MTUinclusion path to cell phones, a second for an MTU inclusion path totablets, and so on. An example of this type of MTU record is shown inFIG. 38B.

Alternatively, the improved computer generates one MTU record for thetouch screen and the record includes a plurality of MTU inclusion pathsections. For example, the MTU record includes an MTU inclusion path forcell phones, an MTU inclusion path for tablets, and so on. An example ofthis type of MTU record is shown in FIG. 39 . The mapping of an MTU toinclusion MTUs and/or to composition MTUs is referred, herein, ascataloging an MTU.

FIG. 38B is a schematic block diagram of an example of auser-interactive graphical representation of an MTU naming and catalogsection of a market-tech unit (MTU) data record of an MTU database. Thissection includes a MTU Name Section, an MTU inclusion section, an MTUFundamental Section, and an MTU Composition Section. The MTU NameSection includes a field for the MTU name. An MTU name is determined bythe improved computer based on an initial technology map that includesthe MTU and/or based on analyzing ingested documents to identify a newMTU and/or to adjust an existing MTU name based on information regardingan existing MTU extracted from the documents.

The MTU Fundamental Section includes a field to indicate whether the MTUis a fundamental MTU or not.

Examples of fundamental elements of the electrical technology categoryare provided with reference to FIG. 40 .

The MTU Inclusion Section includes fields for higher tier MTUs. For anMTU of a touch screen, the tier +1 MTU is input/output HW, the tier +2MTU is a cell phone, the tier +3 MTU is a portable computing device, thetier +4 MTU is a computing device, and the tier +5 MTU is CIE(communication, information, and electrical) technology.

The MTU Composition Section includes fields for tier −1 MTUs. For theexample of a touch screen MTU, the tier −1 −1 MTUs include a touchscreen controller and touch screen sensors.

FIG. 39 is a schematic block diagram of another example of a graphicaluser-interactive representation of an MTU name and catalog section of amarket-tech unit (MTU) data record of an MTU database. In this example,the name and catalog section of an MTU record includes a plurality ofMTU inclusion sections. This enables one MTU record to catalog toplurality of inclusion branches of a technology map.

FIG. 40 is a schematic block diagram of an example of a relationshipbetween CIE (communication, information, and electrical technologies)fundamental hardware (HW) component market-tech units (MTUs), CIE techfundamental HW circuit MTUs, and CIE tech fundamental HW circuit blockMTUs. In general, a fundamental hardware component is comprised ofsingle element such as, for example but not as an exhaustive list, aresistor, capacitor, inductor, transformer, transistor, diode, antenna,battery, electrical conductor, electrical insulator, a transducer, aswitch, a crystal, and a fuse.

In general, a fundamental HW circuit is comprised of two or morefundamental HW components and may further comprise one or more otherfundamental HW circuits. As an example, but not as an exhaustive list, afundamental HW circuit includes an op amp, a voltage reference, acurrent mirror, logic gates, a current source, a clock signal generator,a motor, a generator, a multiplier, an adder, and an RLC analog filter.

In general, a fundamental HW circuit block is comprised of one or morefundamental HW circuits and may further includes one or more fundamentalHW components. As an example, but not as an exhaustive list, afundamental HW circuit block includes an analog to digital converter, adigital to analog converter, a phase locked loop, a voltage controlledoscillator, and a digital filter.

In accordance with the MTU operating system of the improved computer,MTU records for fundamental MTUs do not include MTU inclusion data anddo not include MTU inclusion diagrams. The rationale for this is thatfundamental MTUs are too widely used to map every inclusion use.Fundamental MTUs are, however, referenced by other MTUs in theircomposition data.

FIG. 41 is a schematic block diagram of another example of a graphicaluser interface (GUI) of an improved computer for technology with anentry of “cell phone” for an MTU name. The improved computer determineswhether it has an MTU record for a “cell phone” or a synonym thereof.Synonyms of a cell phone include, but are not limited to mobile phone,smart phone, cellular phone, and cellular telephone.

If an MTU record does not exist for a cell phone, the improved computerstores the term “cell phone” as a potential new MTU term and displays agraphical message that the MTU term of “cell phone” or the like was notfound.

In this example, an MTU record for a cell does exist. In this instance,the improved computer retrieves at least a portion of the MTU record fora cell phone and displays a graphical representation of the cell phoneMTU record as shown in FIG. 42A.

FIG. 42A is a schematic block diagram of another example of auser-interactive graphical representation of a market-tech unit (MTU)data record 452 for a cell phone. As discussed with reference to FIG.38A, the MTU record includes the MTU name & catalog section, the datasection, the technical discussion section, and the diagram sectionpopulated with data regarding a cell phone. More detailed examples ofthe sections of a cell phone MTU are discussed with reference to FIGS.42B through 66 .

FIG. 42B is a schematic block diagram of another example of auser-interactive graphical representation of an MTU name and catalogsection of a cell phone market-tech unit (MTU) data record. In thisexample, the MTU name field includes the phase “cell phone” and the MTUFundamental section indicates that a cell phone is not a fundamentalMTU.

The MTU inclusion section includes the phrase “portable computingdevice” in the MTU tier +1 field; the phrase “computing device” in theMTU tier +2 field; and the phrase “CIE technology” in the MTU tier +3field, where CIE stands for communications, information, and electrical.Note that the MTU inclusion section may include more or less fields formore tier levels (e.g., MTU tier +6) and/or may include more fields perMTU higher tier (e.g., MTU tier +1_1, MTU tier +1_2, etc.).

The MTU composition section includes a plurality of phrases in the MTUtier −1 fields. The phrases includes CP (cell phone) processing, CPmemory, CP communications, CP input/output, CP power management, CPoperating system, CP system applications, CP user applications, CPsystem APIs, and CP user APIs. Note that the MTU composition section mayinclude more or less MTU tier −1 fields than shown and/or may furtherinclude lower MTU tiers (e.g., MTU tier −2, MTU tier −3, etc.)associated with one or more of the MTU tier −1 fields.

FIG. 43 is a schematic block diagram of an example of a user-interactivegraphical MTU inclusion functional diagram of a cell phone market-techunit (MTU) data record. In this MTU inclusion functional diagram for acell phone, the cell phone is one of a plurality of portablecommunication devices that communicate wirelessly via a wirelesscommunication protocol with a wireless communication infrastructure. Theother portable computing devices, which are related MTUs, include asmart watch, a tablet, a laptop, and a 2-way radio.

The wireless communication protocols include one or more satellitecommunication standards and/or protocols, one or more cellularcommunication standards and/or protocols, and WLAN communicationstandards and/or protocols. Note that this example MTU inclusion diagramdoes not illustrate an exhaustive list of wireless communicationstandards and/or protocols nor does it include the various types ofsatellite, cellular, and WLAN communication standards. This example MTUinclusion diagram is intended to illustrate the concept and relativesimplicity of an MTU inclusion diagram. In general, an MTU inclusiondiagram resembles a patent application drawing that illustrates anenvironment in which an MTU of interest (e.g., a cell phone) lies.

The wireless communication infrastructure includes satelliteinfrastructure and terrestrial wireless infrastructure. The terrestrialwireless infrastructure includes cellular infrastructure and WLANinfrastructure, both are coupled to one or more networks.

The MTU inclusion diagram may include related higher tier information.In this diagram, the tier +2 MTUs and the tier +3 MTU are shown. Thetier +3 MTU is the CIE technology MTU. The tier +2 MTUs includes acomputing device, communication protocols, and communicationinfrastructure. The computing device MTU includes the portable computingdevices and fixed computing devices (e.g., personal computers, servers,etc.). The communication protocol MTU includes the wirelesscommunication protocols and wired communication protocols. Thecommunication infrastructure MTU includes the wireless communicationinfrastructure and wired communication infrastructure.

Each symbol that represents an MTU is selectable via graphics userinterface function. If an MTU is selected, the improved computerinterprets the selection and retrieves the corresponding MTU record fromthe MTU database.

FIG. 44 is a schematic block diagram of an example of a user-interactivegraphical MTU inclusion hierarchy diagram of a cell phone market-techunit (MTU) data record. The inclusion hierarchy diagram provides anotherperspective of the tiering of MTUs in a technology map. In this example,a cell phone is a tier −3 MTU, a portable computing device is a tier −2MTU, a computing device is a tier −1 MTU, and the CIE technology is atier 0, or root tier, MTU.

FIG. 45 is a schematic block diagram of an example of a user-interactivegraphical MTU composition functional diagram of a cell phone market-techunit (MTU) data record. A cell phone composition functional diagramincludes the lower tier MTUs of a cell phone, which include a cell phone(CP) operating system, CP system/utility applications, CP userapplications, CP system/utility APIs, CP user APIs, CP processinghardware, CP memory, CP communication hardware, CP input/outputhardware, and CP power management hardware. These MTUs areinterconnected as shown. Note that each MTU symbol is selectable viagraphics user interface function. If an MTU is selected, the improvedcomputer interprets the selection and retrieves the corresponding MTUrecord from the MTU database.

FIG. 46 is a schematic block diagram of an example of a user-interactivegraphical MTU composition hierarchy diagram of a cell phone market-techunit (MTU) data record. The composition hierarchy diagram providesanother perspective of composition tiering of MTUs in a technology map.In this example, a cell phone is a tier −3 MTU, the CP softwareprograms, and CP hardware are tier −4 MTUs. Tier −5 MTUs includes the CPsystem/utilities applications, the CP operating system, the CP userapplications, the CP processing HW, the CP memory, the CP communicationHW, the CP power management HW, and the CP input/output HW. The cellphone APIs are tier −6 MTUs as are CP system applications, CP utilityapplications, and CP user applications.

FIG. 47 is a schematic block diagram of an example of a user-interactivegraphical general description section of a cell phone market-tech unit(MTU) data record. The general description section includes a field forstoring a general and brief description of a cell phone. For example, acell phone is a communication device that wirelessly communications dataand/or voice signals via a cellular communication system with other cellphones and/or other types of communication devices.

FIG. 48 is a schematic block diagram of an example of a user-interactivegraphical MTU synonyms section of a cell phone market-tech unit (MTU)data record. The MTU synonyms section includes a plurality of fields forstoring synonyms of the MTU. For example, a cell phone has the synonymsof mobile phone, smart phone, cellular phone, cellular telephone, mobiledevice, etc.

FIG. 49 is a schematic block diagram of an example of a user-interactivegraphical related MTUs section of a cell phone market-tech unit (MTU)data record. The related MTU section includes a plurality of fields forrelated MTUs, where a related MTU is affiliated with the present MTU viaone or more common inclusion MTUs and/or one or common composition MTUs.Related MTUs to a cell phone include, for example, a computing device, aportable computing device, a smart watch, a tablet, and a laptop.

FIG. 50 is a schematic block diagram of an example of a user-interactivegraphical metadata section of a cell phone market-tech unit (MTU) datarecord. The metadata for an MTU record includes fields for a variety ofdata points regarding the MTU and the documents that support it. Forexample, but not an exhaustive example, the metadata includes date offirst use of the MTU term, date of most recent use, number of datasources used, the history of the MTU, number of MTUs that comprise theMTU, number of lower tiers that comprise the MTU, etc.

FIG. 51 is a schematic block diagram of an example of a user-interactivegraphical science categories section of a cell phone market-tech unit(MTU) data record. This section includes fields for storing thetechnology category in which the MTU lies. The cell phone is in thecommunications, information, and electrical technology categories.

FIG. 52 is a schematic block diagram of an example of a user-interactivegraphical manufacturing data section of a cell phone market-tech unit(MTU) data record. This section includes a plurality of fields formanufacturing data regarding the MTU. For example, but not an exhaustiveexample, the manufacturing data includes manufacturing facilities, theprocesses for manufacturing the MTU, quality control for manufacturingthe MTU, manufacturing equipment for manufacturing the MTU, testprocedures, and test equipment for testing the manufactured MTU.

FIG. 53 is a schematic block diagram of an example of a user-interactivegraphical MSBT (marketing, sales, business, and technical) section of amarket-tech unit (MTU) data record. The MSBT data section includes amarketing data section, an advertising data section, a technology datasection, and a product/service data section. The marketing data sectionincludes fields for a list of marketing materials that relate to thepresent MTU. For each marketing material in the list include its nameand/or title, its source or author, its publication date, and a briefoverview of the subject matter disclosed.

The marketing data section further includes fields for number ofmarketing materials in the list, a list of sources for the marketingmaterials in the list, a summary of the history of marketing the MTU, asummary of the marketing trend of the MTU, a marketing forecast for theMTU, and/or a list marketing features of the MTU identified in themarketing materials. Note that marketing materials include documentsfrom which marketing features were derived and/or documents thatreference a marketable feature and/or documents that reference aspecific product/service in the product/service list.

The advertising section includes fields for a list of advertising (e.g.,sales) materials that relate to the present MTU. For each advertisingmaterial in the list include its name and/or title, its source orauthor, its publication date, and a brief overview of the subject matterdisclosed. The advertising data section further includes fields fornumber of advertising materials in the list, a list of sources for theadvertising materials in the list, a summary of the history ofadvertising the MTU, a summary of the advertising trend of the MTU, anadvertising forecast for the MTU, and/or a list of marketing features ofthe MTU identified in the advertising materials. Note that advertisingmaterials include documents that reference a marketable feature and/ordocuments that reference a specific product/service in theproduct/service list.

The technology data section includes for a list of technical documentsthat relate to the present MTU. For each document in the list includeits name and/or title, its source or author, its publication date, and abrief overview of the subject matter disclosed. The technical datasection further includes fields for number of documents in the list, alist of sources for the documents in the list, a summary of the historyof the technology of the MTU, a summary of the technology trend of theMTU, a technology forecast for the MTU, and/or a list of technicalchallenges of the MTU identified in the documents. Note that technicaldocuments include documents that discuss the technology of the MTU, atechnical aspect of the MTU, and/or a technical use of the MTU or asaspect thereof.

The product/service data section includes fields for a list ofproducts/services that include the MTU. For each product/service in thelist include its name, its provider(s), its public release date, and abrief overview of the product/service. The product/service data sectionfurther includes fields for the number of products/services in the list.The section further includes fields for a list of providers of theproducts/services in the list and the type of provider (e.g.,manufacturer, retailer, wholesaler, broker, distributor, etc.).

The section further includes fields for a list of manufacturers of theMTU; fields for a summary on the history of the products/services;fields for a summary on the history of the providers; fields for asummary on trends of the providers; fields for a trend forecast of theproviders; a summary of the financial history of the products/services;fields for a financial trend of the products/services; fields for afinancial forecast of the products/services; fields for a summary of themarket history regarding the products/services; fields for a markettrend of the products/services; and fields for a market forecast of theproducts/services.

FIG. 54 is a schematic block diagram of an example of a user-interactivegraphical market impact section of a market-tech unit (MTU) data record.The market impact data section includes fields for initial totalavailable market (TAM), initial service obtainable market (SOM),compound annual growth rate (CAGR) of initial TAM and SOM, level ofdisruption in initial TAM, initial TAM life forecast, rate of MTU takingover initial TAM and/or SOM, percentage of takeover of initial TAMand/or SOM, TAM for extended MTU, SOM for extended MTU, CAGR of extendedTAM and SOM, level of disruption in extended TAM by extended MTU,extended TAM life forecast, rate of extended MTU taking over extendedTAM and/or SOM, and percentage of takeover of extended TAM and SOM byextended MTU.

In the example, initial TAM refers to a total available market of an MTUas originally conceived for incorporation in an initial commerciallyviable product/service and initial SOM refers to a service obtainablemarket of the originally conceived MTU. For example, if the originallyconceived MTU is a touch screen for a cell phone, then the initial TAMis the touch screen opportunity for the entire cell phone market and theinitial SOM is the portion of the cell phone market that will mostlikely switch to include a touch screen. The rate of takeover is thetime frame of market adoption, and the percentage of takeover is thepercentage of the market that will adopt products/services with the MTU.

Continuing with the example, the extended MTU includes incorporatingtouch screens in tablets, laptops, and other electronic devices andtouch-based use applications of cell phones, tablets, laptops, and otherelectronic devices. The extended TAM includes the entire cell phonemarket, the entire tablet market, the entire laptop market, and theentire market of the other electronic devices. The extended SOM is theportion of the extended TAM regarding the devices that will most likelyadopt the extended MTU and another portion of the extended TAM for thetouch-based used applications.

FIG. 55 is a schematic block diagram of an example of a user-interactivegraphical MTU boundary section of a market-tech unit (MTU) data record.The MTU boundary section includes fields for a list of unique valuepropositions (UVP), a list of marketable features, a list of technicalchallenges, a list of problems, a list of inventive concepts, a list ofsolutions, a list of inventive embodiments and patent status, a list ofstandards (actual and potential), a list of protocols (actual andpotential), a UVP to marketable feature to tech challenge diagram, atech challenge to problem to inventive embodiment diagram, and MTUpatent landscape data.

As used herein, a unique value proposition (UVP) is a reason forinvesting time and/or money into developing an MTU. There are multiplereasons for investing time and/or money into developing an MTU. Forexample, but not as an exhaustive example, the reasons include betteruser experience, new user experience, improved human-machineinteraction, improve data accuracy, improve data consistency, improvedata organization, improve data interpretation, new product, newservice, improve human health, improve animal health, reduce ecologicaldamage, repair ecological damage, improve recycling of materials, reducemanufacturing costs, improve a manufacturing process, improve safety,improve human performance, and reduce risk of harm.

As is also used herein, a marketable feature is a reason why a consumershould buy, use, etc. a product/service that embodies the MTU. Amarketable feature is often tied to one or more unique valuepropositions and often provides more definitive benefits ofproduct/service that embodies the MTU. For example, marketable featuresfor a UVP of a better user experience for a touch screen include, butnot limited to, more accurate touch detection, better video resolution,better touch movement tracking, etc.

As is further used herein, a tech challenge is a high-level innovationthat is to be created to support a UVP and/or to enable a marketablefeature. For example, for the UVP of a better user experience for touchscreens and its associated marketable features, the tech challengesinclude, but are not limited to, improve signal to noise ratio of touchsensing, improve video graphics processing, and improve touch detectionprocessing and image rendering thereof.

FIG. 56 is a schematic block diagram of an example of interacting with auser-interactive graphical MTU boundary section of a market-tech unit(MTU) data record. As with other user-interactive graphical sections ofa record, the buttons are selectable in this section. In this example,the MTU patent landscape button is selected; which the improved computerinterprets to retrieve and display the patent data section of the MTUrecord as shown in FIG. 57 .

FIG. 57 is a schematic block diagram of an example of a user-interactivegraphical MTU patent data section of a market-tech unit (MTU) datarecord. The patent section includes fields for a list of US patentsregarding the MTU, a number of issued US patents, a list of US patentholders (original assignee and any subsequent assignees), a list of USpatents per patent holder, trends and analysis of the issued US patents(e.g., issuance rate, file to issue time frame, average number of officeactions to final disposition, abandonment rate, etc.), a list of pendingUS patent applications, a number of pending US patent applications, alist of applicants (original assignee and any subsequent assignees) ofthe pending US patent applications, a list of pending US patentapplications per patent applicant, trends and analysis of US patentapplications (e.g., new filings per year, time to first office action,etc.), and a new US patent application filing forecast.

The patent section further includes fields for a list of FN (foreignnational) patents regarding the MTU, a number of issued FN patents, alist of FN patent holders (original assignee and any subsequentassignees), a list of FN patents per patent holder, trends and analysisof the issued FN patents (e.g., issuance rate, file to issue time frame,average number of office actions to final disposition, abandonment rate,etc.), a list of pending FN patent applications, a number of pending FNpatent applications, a list of applicants (original assignee and anysubsequent assignees) of the pending FN patent applications, a list ofpending FN patent applications per patent applicant, trends and analysisof FN patent applications (e.g., new filings per year, time to firstoffice action, etc.), and a new FN patent application filing forecast.

The patent section still further includes fields for a list of pendingPCT (patent cooperation treaty) patent applications regarding the MTU, anumber of pending PCT patent applications, a list of PCT applicants(original assignee and any subsequent assignees) of the pending PCTpatent applications, a list of pending PCT patent applications perapplicant, trends and analysis of CPT patent applications (e.g., newfilings per year, conversion to FN patent applications, number ofcountries for a conversion, etc.), and a new PCT patent applicationfiling forecast.

The patent section yet further includes a list of inventors for thepending patent applications and issued patents regarding the MTU, acomposite list of issued patents (e.g., US and FN) and patent holders,and composite list of pending patent applications (e.g., US, FN, andPCT) and applicants.

FIG. 58 is a schematic block diagram of another example of interactingwith a user-interactive graphical MTU boundary section of a market-techunit (MTU) data record of FIG. 55 . In this example, the interactivebutton regarding the UVP to marketable feature to tech challenge diagramis selected. The improved computer interprets the selection to retrieveand display the UVP to marketable features to tech challenge section asshown in FIG. 59 .

FIG. 59 is a schematic block diagram of an example of interacting with auser-interactive UVP (unique value proposition) to marketable featuresto technology challenges section of a graphical MTU boundary section ofa market-tech unit (MTU) data record. The UVP to marketable features totech challenge section includes a button to select all UVPs, marketablefeatures and tech challenges, a section that lists the unique valuepropositions (UVP) of the MTU, a section that lists the marketablefeatures of the MTU, and a section that lists the tech challenges of theMTU.

For a list of UVPs, marketable features, and tech challenges, anindividual UVP, marketable feature, or tech challenge can be selected.Based the selection, the improved computer would retrieve and display aUVP to market feature to tech challenge diagram for the selected UVP,marketable feature, or tech challenge. As part of the retrievingprocess, the improved computer verifies that the diagram is the mostcurrent version of the diagram and, if not, updates or creates thediagram.

The verification process includes reviewing newly added data to the MTUrecord to determine if it affects a relevant UVP, a relevant marketablefeature, and/or a relevant tech challenge. If the newly added data doesaffect the UVP, the marketable feature, and/or the relevant techchallenge, the improved computer updates the relevant diagram, ordiagrams. Note that each version of a diagram is archived so that ahistorical record of the evaluation of a diagram is maintained. Thisgenerally applies to all diagrams created by the improved computer foran MTU.

In the example of FIG. 59 , the all button is selected, which theimproved computer interprets to retrieve and display a UVP to marketablefeature to tech challenge diagram. An example is shown in FIG. 61 ,which will be subsequently discussed.

FIG. 60 is a schematic block diagram of an example of user-interactivegraphical lists of marketable features, UVP (unique value proposition),and technology challenges of a user-interactive UVP to marketablefeatures to technology challenges section of a graphical MTU boundarysection of a cell phone market-tech unit (MTU) data record. The examplelists are for a cell phone are not intended to be exhaustive lists. Theexample list of UVPs includes maximize battery use technologies,maximize battery charging technologies, incorporate OLED (organic lightemitting diode) display for better video graphics, improve operatingsystem to support a library of user applications, improved 3D(three-dimensions) image processing, and improve touch detection (i.e.,next generation touch sensitivity).

The example list of marketable features includes longer battery use time(e.g., use the phone longer between charges), longer battery life (e.g.,battery lasts longer), better display quality, bigger display, vast userapplication library and ease of adding to the library, better 3D camera,and new & improved touch screen.

The example list of tech challenges includes accurate battery sensing,better battery discharge modeling, better battery charge modeling, OLEDvideo graphics processing, improved operating system process management,file management, etc., new operating system (OS) APIs, improved 3D imagedata gathering, improved 3D data manipulation, improved 3D image datageneration, new touch sensors, and a new touch screen controller.

FIG. 61 is a schematic block diagram of an example of a user-interactiveUVP (unique value proposition) to marketable features to technologychallenges diagram of a graphical MTU boundary section of a cell phonemarket-tech unit (MTU) data record. UVPs are color coded with agray-blue color; marketable features are color coded with a gray-yellowcolor, and tech challenges are color coded with a gray-green color.

The UVPs of maximum battery use technology and maximum battery chargingtechnology underlie the marketable features of improved battery use timeand improved battery life. These UVPs also provide the motivation forthe tech challenges of accurate battery sensing, improved batterydischarge modeling, and improved battery charge modeling.

The OLED display UVP underlies the marketable features of improveddisplay quality and increased display size. This UVP also providesmotivation for the tech challenge of OLED video processing.

The UVP of application orientated operating system underlies themarketable feature of an improved user application library and addingnew applications to it. This UVP also provides motivation for the techchallenges of new OS APIs and new operating system functions of processmanagement, file management, etc.

The UVP of the improved 3D imaging processing underlies the marketablefeature of a better 3D camera. This UVP also provides the motivation forthe tech challenges of 3D image data gathering, 3D image datamanipulation, and 3D image data generation.

The UVP of the next generation touch sensitivity underlies themarketable feature of improved touch screen I/O experiences. This UVPalso provides the motivation for the tech challenges of new touchsensors and a new touch controller.

FIG. 62 is a schematic block diagram of an example of interacting with auser-interactive UVP (unique value proposition) to marketable featuresto technology challenges section of a graphical MTU boundary section ofa market-tech unit (MTU) data record. In this example, the interactivebutton regarding the tech challenge to problem to inventive embodimentdiagram is selected. The improved computer interprets the selection toretrieve and display the tech challenge to problems to inventiveembodiments section as shown in FIG. 63 .

FIG. 63 is a schematic block diagram of an example of a user-interactivetechnology challenges to problems to inventive embodiments section of auser-interactive UVP to marketable features to technology challengessection of a graphical MTU boundary section of a cell phone market-techunit (MTU) data record. This section includes a button for selecting alldiagrams regarding tech challenges to problems to inventive embodiments.

This section includes a list of tech challenges, a list of problems, alist of inventive concepts (IC), a list of solutions, and a list ofinventive embodiments (IE). Each item in a list is represented by aselectable button. For example, each tech challenge (1 through z) isrepresented by a selectable button.

FIG. 64 is a schematic block diagram of an example of user-interactivegraphical lists of technology challenges, problems, and inventiveembodiments of a user-interactive UVP to marketable features totechnology challenges section of a graphical MTU boundary section of acell phone market-tech unit (MTU) data record. The list of techchallenges includes accurate battery sensing, improved battery dischargemodeling, improved battery charge modeling, OLED video processing, newoperating system (OS) APIs, new operating system functions of processingmanagement, file management, etc., improved 3D image data gathering,improved 3D data manipulation, improved 3D image data generation, newtouch sensors, and a new touch screen controller. Each tech challengeprovides motivation for one or more problems.

For example, the tech challenge of accurate battery sensing providesmotivation for the problems of “how to sense a battery with negligibleeffect on the battery” and “how to use a plurality of AC signals tosense a battery”. As another example, the tech challenge of improvedbattery discharge modeling provides motivation for the problem of “howto model battery discharging based on the more accurate sensed batterydata”. As a further example, the tech challenge of improved batterycharge modeling provides motivation for the problem of “how to modelbattery charging based on the more accurate sensed battery data”.

As an even further example, the tech challenge of a new touch controllerprovides motivation for the problem “how to sense a plurality sensorcontemporaneously” and the problem of “how to improve SNR of sensingelectrodes”.

Each problem leads to inventive concepts, with leads to solutions, whichleads to inventive embodiments. Each inventive embodiment is apatentable idea. In this example, the problem of “how to sense a batterywith negligible effect on the battery” leads to the inventiveembodiments of ultra-high SNR sense circuit 1, ultra-high SNR sensecircuit 2, digital processing of high SNR sensed data, sense signalsinjected at the battery cell level, battery level, and/or battery packlevel, and ultra-low loss sense lead line implementations.

As is further included in this example, the problem of “how to improveSNR of sensing electrodes” leads to the inventive embodiments of noiseimmune AFE (analog front end) circuit 1, circuit 2, and circuit 1),narrow band digital filtering, and digital processing of concurrentlysensed data.

FIG. 65 is a schematic block diagram of an example of a user-interactivegraphical representation of a technology challenge to problems toinventive concepts to implementation options to solutions to inventiveembodiments relational map. For a technical challenge, one or moreproblems are identified. The improved computer identifies one or moreproblems for a technical challenge in at least two ways. The first wayis the improved computer identifying problems that are currently beingaddressed based on the supporting data of an MTU. The second way is theimproved computer forecasting problems that are likely to be encounterin addressing the technical challenge based on the supporting data of anMTU, based on technical challenge to problem analytics for theappropriate technology category, or categories, based on scope oftechnical challenge, and/or based on market uses of the MTU supported byat least partially by the technical challenge.

For each problem (currently being addressed and forecasted), theimproved computer identifies one or more inventive concepts. Aninventive concept is a conceptual way of solving the problem. As anexample, for the problem of “improving force transfer between the bodyand the ground via the shoes”, an inventive concept is to have differentforce transfer properties in the heel than in the forefoot of sole toimprove engagement of the foot to the shoe and the shoe to the ground.Another inventive concept for this problem is to have a series ofhorizontal force to vertical force focusing elements in the sole toimprove engagement of the foot to the shoe and the shoe to the ground.

For each inventive concept, the improved computer identifiesimplementation elements, implementation mechanisms, and/orimplementation variants. An implementation element is a tangiblephysical and/or virtual part of an inventive concept. An implementationmechanism is an aspect of an implementation element that can be changed.An implementation variant is a variation of an implementation elementand/or a variation of an implementation mechanism.

As an example, an inventive concept for a problem is “to do X to A, Y toB, and Z to C”. In this example, A, B, and C are implementation elementsand X, Y, and Z are implementation mechanisms. Implementation variantswould be A′ for A, B′ for B, C′ for C, x for X, y for Y, and/or z for Z.

From the implementation elements, the implementation mechanisms, and theimplementation variants, the improved computer identifies one or moresolutions, where a solution is a specific combination of theimplementation elements, the implementation mechanisms, and theimplementation variants. For example, one solution is “do X to A, Y toB, and Z to C”; a second solution is “do x to A, y to B, and z to C”, athird solution is “do X to A”, Y to B′, and Z to C′ “, and fourthsolution is “do x to A′, y to B′, and z to C′ “.

For a solution, the improved computer identifies a set of noveltynuggets (e.g., a technical aspect to is believed to be novel in light ofknown prior art. Depending on the nature of the novelty nuggets, theimproved computer identifies one or more inventive embodiments, where aninventive embodiment represents a patentable invention.

Continuing with the above example, for the first solution of do X to A,Y to B, and Z to C”, the improved computer identifies the noveltynuggets of “do X to A”, “do Y to B”, and “do Z to C”. The improvedcomputer then identifies specific combinations of the novelty nuggets toproduce the inventive embodiments. For the present example, the improvedcomputer determines that the combination of “do X to A” and “do Z to C”is an invention embodiment and “do Y to B” is a separate inventiveembodiment.

The improved computer then determines an invention type for each of theinventive embodiments. As discussed with reference to FIG. 19 ,invention types include fundamental, commercially necessary, commercialexpansion, new fundamental, commercial expansion regarding new uses offundamental inventions, commercial expansion of new fundamentalinventions, commercial expansion regarding vertical integration,commercial expansion regarding horizontal integration, commercialexpansion regarding competitor speed bump, commercial expansionregarding potential standard essential, and/or commercial expansionregarding potential non-essential but commercially necessary standardsrelated.

The improved computer routinely updates the technical challenge toinventive embodiment relational map as it ingests new data. Eachprevious version of a technical challenge to inventive embodimentrelational map archived to form a historical evolution of the map.

The collection of technical to inventive embodiment relational maps ofan MTU provide the improved computer with a mechanism for determiningthe total number of inventions to be created over the life of an MTU,with a mechanism to target particular inventions.

The conventional patent process does not support and does not create acollection of technical to inventive embodiment relational maps for anMTU. Without such maps and/or without quantifying technology via MTUs,there are no viable mechanisms to determine how well a product is patentprotected until a patent dispute arises years after the bulk of theinventing has been completed and to opportunity to patent protect it haspassed. Further, without such maps, it is very difficult to determinehow well a patent, or patents, cover design-around options. For example,there may be 10 or more inventive embodiments for a particular problem.One or two patents addressing the problem leaves too many design aroundoptions open, which significantly diminishes the value of the one or twopatents.

Such maps would be extremely helpful in determining whether to invest ina technology company. The maps illustrate the level of innovation likelyrequired to bring a MTU to market, to obtain market adoption, and toobtain sustained market success. The maps further illustrate, at thetime of investment, the level of patent protection obtained to date andits level of sufficiency. Interpretation of the maps indicate, for theinventions not patent protected, if the opportunity has passed. Inaddition, interpretation of the maps further indicate the level ofpatent protection that is needed to obtain a desired patent position forthe MTU.

A list of generalized examples of tech challenges for communication,electrical, and/or information technologies include too costly, operatestoo slow, needs improved reliability, needs improved efficiency, needsimproved accuracy, needs improved security, needs improved safety, needsimproved user experiences, needs new user experiences, needs newoperations/features, needs improved operations/features, needs newsecurity, and needs new safety.

FIG. 66 is a schematic block diagram of an example of a user-interactivegraphical MTU composition functional diagram of a cell phone market-techunit (MTU) data record with the interactive button for input/output HWbeing selected. The improved computer interprets the selection toretrieve and display the MTU record a cell phones input/output HW.

FIG. 67 is a schematic block diagram of an example of a user-interactivegraphical market-tech unit (MTU) data record for input/output hardware(HW) of a cell phone as selected in FIG. 66 . In accordance with theformatting of MTU records, the input/output HW MTU record 452-1 includesan MTU name & catalog section, a data section for data relevant to acell phone's input/output HW, a technical discussion section, and adiagram section.

FIG. 68 is a schematic block diagram of an example of a user-interactivegraphical input/output hardware (CP 10 HW) of a cell phone inclusivefunctional diagram of the MTU record of FIG. 67 . Note that the CP 10 HWinclusion functional diagram is the same as the cell phone compositionfunctional diagram. Similarly, as shown in FIG. 69 , the CP 10 HWinclusion hierarchy diagram is the same as the cell phone compositionhierarchy diagram. This generally holds for MTUs of sequential tiers. Ingeneral, the inclusion diagrams for an MTU at tier “i” are the same asthe composition diagrams for a tier “i+1” MTU that is in the inclusiondiagrams of the MTU.

FIG. 70 is a schematic block diagram of an example of a user-interactivegraphical input/output hardware (HW) of a cell phone compositionfunctional diagram. The functional diagram of the cell phone′s IOhardware includes an IO and/or peripheral control module, acommunication interface, an IO interface, an output interface, outputdevices (e.g., a display, a speaker, etc.), an input interface, inputdevices (e.g., a touch screen, a microphone, switches, a camera, etc.),and secondary memory interface intercoupled as shown.

FIG. 71 is a schematic block diagram of an example of a user-interactivegraphical input/output hardware (HW) of a cell phone compositionhierarchy diagram. In this diagram, the highest tier is the IO hardware,the next lower tier includes the communication interface, and the otherinterfaces. The next lower tier includes secondary memory, user outputdevices (e.g., display, speaker, etc.), user input devices (touchscreen, microphone, switches, camera, etc.), and communication devices(cellular, WLAN, Bluetooth, etc.).

FIG. 72 is a schematic block diagram of an example of a user-interactivegraphical MTU name & catalog section of a market-tech unit (MTU) datarecord for input/output hardware (HW) of a cell phone. In accordancewith the formatting of MTU records, the MTU name & catalog sectionincludes an MTU name section, an MTU inclusion section, an MTUfundamental section, and an MTU composition section.

The MTU name section includes the name for this MTU, which isinput/output HW. The MTU inclusion section includes the tier +1 MTU ofcell phone, the tier +2 MTU of portable computing device, the tier +3MTU of computing device, and the tier +4 MTU of CIE technology.

The MTU fundamental section indicates that the input/output HW is not afundamental MTU. The MTU composition section includes, at a tier −1level, the secondary memory interface, the secondary memory, thecommunication interface, communication devices, the input interface,input devices, the output interface, and output devices.

FIG. 73 is a schematic block diagram of an example of a user-interactivegraphical cell phone composition functional diagram with “tier −2”details. This functional diagram of a cell phone includes the tier −1MTUs and their respective tier −2 MTUs. The CP memory MTU includes a ROMMTU, a main memory MTU, a cache MTU, and a secondary memory MTU. The CPprocessing MTU includes a core control module MTU, a processing moduleMTU, and a video graphics processing MTU. The CP communication MTUincludes a WLAN transceiver MTU, a cellular transceiver MTU, andBluetooth (BT) transceiver MTU. The CP input/output HW includes the tier−2 MTUs as discussed with reference to FIG. 70 .

From this diagram, the user input device of touchscreen is selected. Theimproved computer interprets the selection to retrieve and display anMTU record of the touchscreen; an example of which is shown in FIG. 74 .

FIG. 74 is a schematic block diagram of an example of a user-interactivegraphical market-tech unit (MTU) data record for a touch screen ofinput/output hardware (HW) of a cell phone. In accordance with theformatting of MTU records, the touchscreen MTU records 452-2 includes anMTU name & catalog section, a data section for data relevant to atouchscreen of an input/output hardware of a cell phone, a technicaldiscussion section, and a diagram section.

FIG. 75 is a schematic block diagram of an example of a user-interactivegraphical composition functional diagram of a touch screen ofinput/output hardware (HW) of a cell phone. The touch screen includesthe lower tier MTUs of a touch sense controller and touch sensors, whichare interconnected as shown.

FIG. 76 is a schematic block diagram of an example of a user-interactivegraphical MTU name & catalog section of a market-tech unit (MTU) datarecord for a touch screen of input/output hardware (HW) of a cell phone.The MTU name for this record is touchscreen. The MTU fundamental sectionindicates that this is not a fundamental MTU.

The MTU inclusion section includes a tier +1 MTU of the input/output HW,a tier +2 MTU of the cell phone, a tier +3 MTU of portable computingdevice, a tier +4 MTU of computing device, and a tier +5 MTU of CIEtechnology. The MTU composition section includes the lower tier MTUs oftouch sense controller and touch sensors.

From FIG. 75 , the touch screen controller was selected. The improvedcomputer interprets the selection to retrieve and display an MTU recordof a touch screen controller; an example of which is shown in FIG. 77 .

FIG. 77 is a schematic block diagram of an example of a user-interactivegraphical market-tech unit (MTU) data record for a touch screencontroller of a touch screen of input/output hardware (HW) of a cellphone. In accordance with the formatting of MTU records, the touchscreen controller MTU record 452-3 includes an MTU name & catalogsection, a data section for data relevant to a touchscreen of aninput/output hardware of a cell phone, a technical discussion section,and a diagram section.

FIG. 78 is a schematic block diagram of an example of a user-interactivegraphical composition functional diagram of a touch screen controller ofa touch screen of input/output hardware (HW) of a cell phone. The touchsense controller includes a touch processing circuit and a plurality ofsensor circuits.

FIG. 79 is a schematic block diagram of an example of a user-interactivegraphical MTU name & catalog section of a market-tech unit (MTU) datarecord for a touch screen controller of a touch screen of input/outputhardware (HW) of a cell phone. The MTU name for this record is touchsense controller. The MTU fundamental section indicates that this is nota fundamental MTU.

The MTU inclusion section includes a tier +1 MTU of touch screen, a tier+2 MTU of the input/output HW, a tier +3 MTU of the cell phone, a tier+4 MTU of portable computing device, and a tier +5 MTU of computingdevice. The MTU composition section includes the lower tier MTUs ofsensor circuit and touch processing circuit.

FIG. 80 is a schematic block diagram of an example of a user-interactivegraphical composition functional diagram of a touch screen ofinput/output hardware (HW) of a cell phone with “tier −2” details. Thediagram includes a touch sense controller and a plurality of electrodes,which functions as sensors. The touch sense controller includes aplurality of sensor circuits and a touch processing circuit.

In general, a sensor circuit provides a signal to a correspondingelectrode so that it can measure the self-capacitance of the electrode(e.g., capacitance of the electrode with respect to a ground plane)and/or mutual capacitance of the electrode with respect to anintersecting electrode. Changes in the self-capacitance and/or mutualcapacitance indicates a human touch (directly or via a stylus) of theelectrode.

The touch processing circuit receives the sensed capacitance values fromthe sensor circuits. The touch screen processing circuit detects a touchbased on capacitance changes of electrodes and the position of the touchbased on which electrodes have a capacitance change.

In this Figure, the sensor circuit is selected for further detail. Theimproved computer interprets the selection to retrieve and display anMTU record of a sensor circuit; an example of which is shown in FIG. 81.

FIG. 81 is a schematic block diagram of an example of a user-interactivegraphical market-tech unit (MTU) data record for a sensor circuit of atouch screen controller of a touch screen of input/output hardware (HW)of a cell phone. In accordance with the formatting of MTU records, thesensor circuit MTU record 452-4 includes an MTU name & catalog section,a data section for data relevant to a touchscreen of an input/outputhardware of a cell phone, a technical discussion section, and a diagramsection.

FIG. 82 is a schematic block diagram of an example of a user-interactivegraphical composition functional diagram of a sensor circuit of a touchscreen controller of a touch screen of input/output hardware (HW) of acell phone. The sensor circuit includes a sense circuit, a drivecircuit, a digital filter, and digital processing circuit.

The drive circuit provides a drive signal to an electrode. The sensecircuit senses the impedance and/or capacitance of the electrode andproduces a digital representation thereof. The digital filter filtersthe digital representation to remove unwanted signal components toproduce digital values. The digital processing circuit interprets thedigitals to provide a sensed value at a sampling rate to the touchprocessing circuit.

In this Figure, the sense circuit of the sensor circuit is selected forfurther detail. The improved computer interprets the selection toretrieve and display an MTU record of a sense circuit; an example ofwhich is shown in FIG. 84 , which is discussed in turn.

FIG. 83 is a schematic block diagram of an example of a user-interactivegraphical MTU name & catalog section of a market-tech unit (MTU) datarecord for a sensor circuit of a touch screen controller of a touchscreen of input/output hardware (HW) of a cell phone. The MTU name forthis record is sensor circuit. The MTU fundamental section indicatesthat this is not a fundamental MTU.

The MTU inclusion section includes a tier +1 MTU of a touch screencontroller, a tier +2 MTU of touch screen, a tier +3 MTU of theinput/output HW, a tier +4 MTU of the cell phone, and a tier +5 MTU ofportable computing device. The MTU composition section includes thelower tier MTUs of sense circuit, a drive circuit, a sense digitalfilter, and sense digital processing circuit.

FIG. 84 is a schematic block diagram of an example of a user-interactivegraphical market-tech unit (MTU) data record for a sense circuit of asensor circuit of a touch screen controller of a touch screen ofinput/output hardware (HW) of a cell phone. In accordance with theformatting of MTU records, the sense circuit MTU record 452-5 includesan MTU name & catalog section, a data section for data relevant to atouchscreen of an input/output hardware of a cell phone, a technicaldiscussion section, and a diagram section.

FIG. 85 is a schematic block diagram of an example of a user-interactivegraphical composition functional diagram of a sense circuit of a sensorcircuit of a touch screen controller of a touch screen of input/outputhardware (HW) of a cell phone. The sense circuit includes an op amp, afeedback circuit (which could be part of the op amp), a voltagereference source, and an analog to digital converter (ADC). The op ampcompares a reference voltage produced by the voltage reference sourcewith a voltage imposed on electrode by the drive circuit to produce ananalog signal that represents a difference between the reference voltageand the voltage on the electrode. The ADC converts the analog signalinto a digital signal.

FIG. 86 is a schematic block diagram of an example of a user-interactivegraphical MTU name & catalog section of a market-tech unit (MTU) datarecord for a sense circuit of a sensor circuit of a touch screencontroller of a touch screen of input/output hardware (HW) of a cellphone. The MTU name for this record is sense circuit [of a sensorcircuit]. The MTU fundamental section indicates that this is not afundamental MTU.

The MTU inclusion section includes a tier +1 MTU of a sensor circuit, atier +2 MTU of a touch screen controller, a tier +3 MTU of touch screen,a tier +4 MTU of the input/output HW, and a tier +5 MTU of the cellphone. The MTU composition section includes the lower tier MTUs of an opamp, an ADC, a feedback circuit, and a reference signal generator (orreference voltage source).

FIG. 87 is a schematic block diagram of an example of a user-interactivegraphical composition functional diagram of a sensor circuit of a touchscreen of input/output hardware (HW) of a cell phone with “tier −2”details. This diagram includes the MTU elements of the drive circuit andof the sense circuit. The drive circuit includes a signal source, adriver (D), and an impedance (Z).

FIG. 88 is a schematic block diagram of an example of a user-interactivegraphical market-tech unit (MTU) data record for an analog to digitalconverter. In accordance with the formatting of MTU records, the ADC MTUrecord 452-6 includes an MTU name & catalog section, a data section fordata relevant to a touchscreen of an input/output hardware of a cellphone, a technical discussion section, and a diagram section.

FIG. 89 is a schematic block diagram of an example of a user-interactivegraphical composition functional diagram of an analog to digitalconverter. The ADC includes an analog comparison circuit and a digitallogic circuit. The analog comparison circuit compares an analog inputwith one or more reference voltage to produce analog comparative signal.

For example, if the ADC includes three reference voltages (e.g., 1 volt,2 volts, and 3 volts), for an input voltage below 1 volt, the analogcomparator produce a 0 VDC output. If the input voltage is between 1 and2 volts, the analog comparator produce a 1 VDC output. If the inputvoltage is between 2 and 3 volts, the analog comparator produce a 2 VDCoutput. If the input voltage is above 3 volts, the analog comparatorproduce a 3 VDC output.

The digital logic circuit, at a sampling rate, produces a digitalrepresentation of the analog output of the analog comparator. In theabove example, the digital logic circuit produces a 00 digital value foran analog output of 0 volts, a 01 digital value for an analog output of1 volt, a 10 digital value for an analog output of 2 volts, and a 11digital value for an analog output of 3 volts.

FIG. 90 is a schematic block diagram of an example of a user-interactivegraphical MTU naming & catalog section of a market-tech unit (MTU) datarecord for an analog to digital converter, which is a fundamental MTU.The MTU name for this record is analog to digital converter. The MTUfundamental section indicates that this is a fundamental MTU. Being afundamental MTU, the MTU inclusion section is left blank. The MTUcomposition section includes the lower tier MTUs of an analog comparecircuit and a digital logic circuit.

FIG. 91 is a schematic block diagram of an example of a user-interactivegraphical market-tech unit (MTU) data records for MTUs related to thesense circuit of a sensor circuit of a touch screen controller of atouch screen of input/output hardware (HW) of a cell phone. The relatedMTU records include one for a laptop, one for a tablet, and one for asmart watch.

Related MTUs are useful in expanding an initial MTU. For example, a newtouch screen controller designed for a touch screen for use in a cellphone may be expanded to uses in the related MTUs of tablets, laptops,and/or smart watches.

FIG. 92 is a schematic block diagram of an example of a user-interactivegraphical market-tech unit (MTU) data record for a touch sensecontroller that includes a plurality of MTU inclusion sections asopposed to separate MTU records for the touch screen controller and itsdifferent MTU inclusion paths.

In this MTU records, the MTU name and catalog section includes aplurality of MTU includes sections. The first MTU inclusion section isfor a cell phone, the second MTU section is for a laptop, the third MTUinclusion section is for a tablet, and the fourth MTU inclusion sectionis for a smart watch.

FIG. 93 is a schematic block diagram of an example of a user-interactivegraphical composition functional diagram of expanded use of a sensorcircuit of a touch sense controller. The sensor circuit is shown to beincluded in a touch sense controller of a touch screen. The touch screencan be used in portable computing devices as discussed. A touch screencan also be used in a fixed computing device, a monitor, an interactivedisplay, and/or a physical access control unit.

If the improved computer determines that the new sensor circuit enablesnew functionalities in the fixed computing device, a monitor, aninteractive display, and/or a physical access control unit, the improvedcomputer extends the use of the sensor circuit to in the particular usecases.

As another technique for extending the sensor circuit MTU, the improvedcomputer looks to other circuitry that uses a form of sensing sensors.In this example, the improved computer looks to human-machine interface(analog world to digital world), biometric sensing, moisture sensing,temperature sensing, and pressure sense as a few examples. The improvedcomputer determines whether the new sensor circuit would improveperformance of the other sensing applications. If so, the improvedcomputer expands the MTU market impact and technical reach to includeeach of the other sensing applications.

To further expand the sensor circuit MTU, the improved computer analyzesthe sensor circuit of FIG. 82 regarding its overall function and thefunction of its MTU components. The overall function of the sensorcircuit is to capture a signal that represents a capacitance of anelectrode. The function of the drive circuit is to provide a voltagedrive signal to the electrode and the function of the sense circuit isto a sense a voltage produced by the electrode in response to thevoltage drive signal. The function of the digital filter and digitalprocessing is to convert a digital representation of the sensed voltageinto a digital representation of capacitance.

Based on the overall function and the function of the sensor circuitscomponents, the improved computer searches it system databases for othersensor circuits, for other sensors, and/or for other sensing functions.For example, from the searching, the improved computer learns that thereare a variety of drive signal options, a variety of characteristics of asensor that can be sensed, and a variety of conditions that can besensed.

As shown in FIG. 94B, the drive signal options include a DC voltagedrive signal, an AC voltage drive signal, a DC current drive signal, anAC current drive signal, an infrared (IR) drive signal, and an acousticdrive signal. The sensing characteristics include capacitance, voltage,resistance, current, phase, magnitude, frequency, and time. Theconditions includes temperature, pressure, impedance, resistance, gaslevel, moisture, velocity, proximity, flow rate, and distance.

From these options, the improved computer determines which of them areviable options for the sensor circuit of a touch screen controller. Thedetermined options are highlighted by the gray shaded boxes. In additionto determining further functional options, the improved computergenerates a more generic composition functional diagram of a sensorcircuit as shown in FIG. 94A. As shown, the sensor circuit is coupled toa generic sensor and includes a sense circuit, a drive circuit, and adigital sensed signal to sensed condition circuit.

The improved computer applies the determined options to the sensordiagram and the technical challenge to inventive embodiment, which isalso shown in FIG. 94B. This enables the improved computer to expand thesensor circuit of a touch screen controller in two ways: expanding thetechnical aspects of the sensor circuit based on the determined optionsand expand its uses based on uses of the other sensor circuits theimproved computer identified. The technical challenge is expanded fromsensing an electrode to sensing for temperature, pressure, impedance,gas levels, and moisture, which also expands the list of problems andinventive embodiments.

The different drive signal options and the different sensecharacteristics adds the implementation elements, the implementationmechanisms, and/or the implementation variants, which includes the listof solutions and the list of inventive embodiments.

As another example of the improved computer expanding the technicalaspects of an initial MTU and expanding its uses, consider the baseballshoe 460 of FIG. 95 , which includes the force transfer sole 465 of FIG.96 . The original unique value proposition for the new baseball shoe wasto help baseball players feel more stable and more connected to theground. The original technical challenge was “how to improve theground-body connection through a pair of baseball shoes”, which was alsothe initial problem.

The baseball shoe 460 includes an upper section 462 that is attached toa midsole 464, and an outsole 466. Not shown is an insole, which ispositioned within the upper section 462 and above (e.g., closer to thefoot) the midsole 464. The midsole 464 as shown in FIG. 96 includes aheel section 468 and a forefoot section 467 and is shown in block formfor ease of illustration. In practice, the shape of the midsole 464conforms to the shape of the baseball shoe 460.

The inventive concept for the problem of improving the ground-bodyconnection through a pair of baseball shoes includes using materialsthat have different force transfer properties in the heel than in theforefoot of midsole to improve engagement of the foot to the shoe andthe shoe to the ground.

With the conventional patent process, it is most likely that a patentapplication would have been filed regarding a baseball shoe thatincludes materials that have different force transfer properties in theheel than in the forefoot of midsole to improve engagement of the footto the shoe and the shoe to the ground. Once the patent applicationissued, it is a 50-50 chance that a continuation patent applicationwould be filed. In this scenario, the innovation of improving theground-body connection through shoes is woefully under patented, whichresults in a significant loss of value.

For the innovation of improving the ground-body connection throughshoes, the improved computer determines a complete picture of the patentopportunity for innovation and its likely value as the patentopportunity is realized (e.g., as the architectural plan to patentprotect the innovative technology is patent protected).

To begin, the improved computer retrieves one or more relevanttechnology maps for the innovation. For this example, the improvedcomputer retrieves the technology map for baseball shoes as shown inFIG. 97 . The technology map includes the MTU of a baseball shoe, whichincludes the composition MTUs of an upper section, an insole, a midsole,and an outsole. The outsole MTU includes composition MTUs of metalspikes, molded cleats, and spikeless turf.

The technology map includes the inclusion MTU of athletic shoes for thebaseball shoe MTU and the inclusion MTU of footwear for the athleticshoe MTU. The map further includes related MTUs of the baseball shoeMTU. The related MTUs are for running shoes, fitness shoes, basketballshoes, golf shoes, tennis shoes, and other types of athletic shoes.

The map also includes related MTUs for the athletic shoe MTUs. Theserelated MTUs includes casual shoes, leather shoes, and textile & others.The composition MTUs for the casual shoes MTU are shown as sandals andsneakers. The composition MTUs for the leather shoe MTU are shown asdress shoes and cowboy boots. The composition MTUs for the textile &other shoe MTU are shown as work shoes and work boots.

The technology map further includes related MTUs for the footwear MTU.They include skates, ski boots, socks, and custom insoles. The mapfurther includes for some of the MTUs an indication of annual US salesor a percentage of the US market. For example, footwear sales in 2019 inthe US was approximately $130 billion and the custom insole sales in2019 in the US was approximately $2 billion.

Of the $130 billion footwear sales, approximately $21 billion was fromcasual shoes, $15 billion from athletic shoes, $43 billion from leathershoes, and $51 billion from textile & other shoes. Within the athleticshoe market, running shoes typically account for 30% of sales, fitnessshoes about 30%, basketball shoes about 20%, baseball shoes about 4%,golf shoes about 6%, tennis shoes about 6%, and other athletic shoesabout 4%. As such, the US market for baseball shoes is approximately a$600 million per year.

Note that this example technology map is not intended to provide anexhaustive list of composition MTUs and/or inclusion MTUs. It isprovided to illustrate some of the functional abilities of the improvedcomputer for technology.

The example continues with the improved computer adding a new MTUregarding a force transfer midsole of a baseball shoe to the technologymap as shown in FIG. 98 . The new MTU is shown as a black shaded box andthe next level MTUs are highlighted in gray shaded boxes.

With this as a starting point, the improved computer begins to expandthe force transfer midsole of a baseball shoe MTU. For example, theimproved computer determines whether the force transfer innovation for amidsole can be applied to the insole and/or outsole. In this example,the innovation can be applied to the related MTUs of the midsole (i.e.,the insole and outsole) as shown in FIG. 99 .

The improved computer then determines whether the force transferinnovation can be applied to the related MTUs of the baseball shoe MTU.In this example, the innovation is applicable to insoles, midsoles,and/or outsoles of running shoes, fitness shoes, basketball shoes, golfshoes, tennis shoes, and other types of athletic shoes. In thisinstance, innovation is applicable to all athletic shoes as shown inFIG. 100 .

The improved computer then determines whether the force transferinnovation can be applied to the related MTUs of the athletic shoes MTU.In this example, the innovation is applicable to insoles, midsoles,and/or outsoles of casual shoes, leather shoes, and textile & othershoes. For each of the related MTUs for which the innovation isapplicable, the improved computer determines which of its compositionMTUs the innovation can be applied. For casual shoes, it is applicableto sandals and sneaker; for leather shoes, it is applicable to dressshoes; and for textile & other shoes, it is applicable to work shoes andwork boots as is shown in FIG. 101 .

The improved computer then determines whether the force transferinnovation can be applied to the related MTUs of the footwear MTU. Inthis example, the force transfer innovation is applicable to skates, skiboots and custom insoles as shown in FIG. 102 . FIG. 102 illustrates thecomplete expansion of the inventive concept of force transfer of abaseball shoe's midsole.

The improved computer then focuses on determining the total number ofinventions for the innovation in light of the expanded use and inventiveconcepts discussed above. With reference to FIG. 103 , the improvedcomputer labels the problem as “improving the ground-body connectionthrough footwear”. The improved computer would create a separate problemto inventive embodiment mapping for skates, another for ski boots, andanother for custom insoles.

For the footwear problem, the improved computer identifies (determines,creates, and/or retrieves) one or more inventive concepts. A firstinventive concept includes “providing different force transferproperties in the heel section than in the forefoot section”. A secondinventive concept includes “a series of horizontal force to verticalforce focusing elements in the midsole and/or outsole”.

For the first inventive concept, the improved computer identifies(determines, creates, and/or retrieves) one or more implementationelements, one or more implementation mechanisms, and/or one or moreimplementation variants. In this example, the improved computeridentifies insole, midsole, and outsole as implementation elements;contours, dimensions, and materials as implementation mechanisms; andfixed force transfer, adjustable force transfer, and dynamic forcetransfer as implementation variants as shown in FIG. 104 .

The improved computer then identifies (determines, creates, and/orretrieves) one or more solutions from the one or more implementationelements, the one or more implementation mechanisms, and/or the one ormore implementation variants. As shown in FIG. 105 , the improvedcomputer identifies multiple solutions via different combinations of theimplementation elements, implementation mechanisms, and implementationvariants. For example, but not as an exhaustive example, a firstsolution regarding a contour focus to obtain fixed force transfer viainsole, midsole, &/or outsole; a second solution regarding a dimensionsfocus to obtain fixed force transfer via insole, midsole, &/or outsole,and another solution regarding a material focus to obtain dynamic forcetransfer via insole, midsole, &/or outsole.

For the first solution as shown in FIG. 106 , the improved computeridentifies (determines, creates, and/or retrieves) one or more inventiveembodiments based on novelty nuggets of the solution. For the firstinvention of “contour focus to obtain fixed forced transfer via insole,midsole, &/or outsole”, the novelty nuggets include a first contour(e.g., surface gradient related to the bottom of a foot, slopes, pitch,etc.) in heel insole, midsole, and/or outsole, and a second contour inforefoot insole, midsole, and/or outsole.

The inventive embodiments include different combinations of noveltynuggets. For example, one inventive embodiment includes the firstcontour of the heel section in the insole, midsole, and/or outsole, andthe second contour of the forefoot in the midsole for a fixed forcetransfer. A second inventive embodiment includes the first contour ofthe heel section in the midsole, and the second contour of the forefootin the insole, midsole, and/or outsole for fixed transfer.

Other inventive embodiments from the various solutions include, but notlimited to, a first set of materials for the heel section in the insole,midsole, and/or outsole, and second set of materials of the forefoot inthe midsole for a fixed force transfer, where a set includes one or morematerials; a first varying material composition for the heel section inthe insole, midsole, and/or outsole, and second varying materialcomposition of the forefoot in the midsole for a dynamic force transferbased on orientation of weight force vectors; and a first adjustablematerial composition for the heel section in the insole, midsole, and/oroutsole, and second adjustable material composition of the forefoot inthe midsole for an adjustable force transfer to accommodate differentsized persons wearing the shoes.

The improved computer then determines an architectural plan for patentprotecting the force transfer innovation in footwear, skates, ski boots,and/or custom insoles. The improved computer also calculates the expenseand growth of the patent protection of the force transfer innovation ona year-by-year basis as the architectural plan is executed.

The improved computer also calculates the value of the innovation on ayear-by-year basis, which is predicated on the market value of thefootwear industry, the market value of the skates industry, the marketvalue of the ski boots industry, and/or the market value of the custominsole industry. With the conventional patent process, one or twopatents would have likely been obtained for a baseball shoe having afixed forced transfer midsole. The baseball market is about $600 millionin annual revenue. Via the improved computer, dozens of patents coveringa variety of implementation across of all footwear would be obtained.The footwear market is about $130 billion in annual revenue; that is216.67 times larger than the baseball shoe market. As an example, thevalue of force transfer technology if conventionally patented would beabout $500K to $1 million; and the value of force transfer technologyusing the re-engineered patent process and the functionality of theimproved computer is about $100 million, which is 100× to 200× increasein value.

FIG. 107 is a schematic block diagram of an example of the data thatcomprises a market-tech unit (MTU) data record in an MTU database. For amarket tech unit (MTU) record, a plethora of data is routinelycollected, processed, and organized by the improved computer toestablish technical boundaries for the MTU, to determine technicalexpansion of the MTU, to determine market use expansion of the MTU, todetermine market impact of the MTU, to determine value of the MTU, todetermine inventions to be patent protected, to determine anarchitectural plan to patent protect the MTU, to track execution of thearchitectural plan, to determine use opportunities for the patented MTU,to determine an existing patent landscape, to determine an existingcompetitor landscape, to determine an existing product/servicelandscape, to determine a future forecasted patent landscape, todetermine a future forecasted competitor landscape, and/or to determinea future forecasted product/service landscape.

The data for an MTU record is organized by MTU inclusion (higher tiers)services, MTU inclusion products, MTU services, MTU products, MTUproduct/service financial performance, MTU product/service marketopportunity, MTU market expansion opportunity, MTU innovation &innovation expansion opportunity, MTU patenting, MTU value, and thesupporting documents from which the data is extracted. Each of the datasections includes a past & current component and a future forecastedcomponent. The products and service data sections further includes alist of providers. The patenting data section further includes a list ofpatent holders (e.g., applicants and/or assignees).

FIG. 108 is a schematic block diagram of another embodiment of a portionof an improved computer for technology 70 that functions to ingest,dissect, interpret, extract data from documents (e.g., marketing, sales,business, technology, patents, and/or other relevant types ofdocuments), to store such extracted data, to store the documents, toidentify and create MTUs, and to update MTU records in accordance withnew data. The portion of the improved computer includes the computingentity operation system 104, the MTU operating system 106, some of thesystem databases 74, co-processors of the hardware section, thecommunication interface hardware, and a plurality of MTU systemapplications 470. The system databases includes the MSBT database 262,the MTU database 264, the patent terms database 266, and the annotatedpatent database 268.

The MTU system applications 470 includes MSBTP system applications,correlation applications, and cataloging applications. The MSBTP(marketing, sales, business, technology, and patents) systemapplications includes patent data identify & gather application, patentdata dissection & MTU interpret application, patent data record creationapplication, MSBT data identify & gather application, MSBT datadissection & MTU interpret application, MSBT data record creationapplication.

The correlation applications include MTU tagging of a patent documentapplication and MTU tagging of an MSBT document application. Thecataloging applications include MTU inclusion mapping application, MTUinclusion diagram generating application, MTU inclusion technicaldiscussion application, MTU composition mapping application, MTUcomposition diagram generating application, and MTU compositiontechnical discussion application.

The MTU operating system 106 includes the MTU correlation OS function,the MTU processing management function, the MTU system databasemanagement function, and the MTU error detection and managementfunction. The co-processors include the MSBT ingest & MTU classify unit280, the MTU identify, create, and data populate unit 282, the MTUcataloging unit 284, the patent annotating unit 292, and the MTUcorrelation unit 286. The communication hardware connects the improvedcomputer to one or more networks (e.g., Internet, WAN, LAN, WLAN,cellular, etc.).

The various co-processors execute the various MTU system applicationsand corresponding portions of the MTU operating system 106 and computingentity operating system 104 as further described with reference to FIGS.109 through 150C.

FIG. 109 is a schematic block diagram of an embodiment of an MSBTP(marketing, sales, business, technology, and patent) data gatheringsection 72 of an improved computer for technology. The section 72includes the MTU correlation unit 286, the MTU cataloging unit 284, theMTU identify, create, and data populate unit 282, the MSBT ingest & MTUclassify unit 280, the patent term recognition unit 290, and the patentannotating unit 292.

The MSBT ingest & MTU classify unit 280 receives MSBT documents (e.g.,marketing, sales, business, technology, patents, and/or other relevanttypes of documents). The unit dissects (e.g., breaks down, analyzes) thedocument according to data of interest regarding MTUs (e.g., the datathat is placed into an MTU record). For example, a document ispartitioned into sections based on the data of interest regarding MTUs.As a specific example, one or more portions are sectioned as beingrelated to a marketable feature of a product and/or service, another oneor more portions are sectioned as being related to a technicaldescription, and yet another one or more portions are sectioned as beingrelated to financial information of a product and/or service.

The unit 280 extracts data from the various portions of based on thetype of section. For example, financial data is extracted for portionssectioned as financial, marketable feature data is extracted fromportions sectioned as marketable feature, and so on.

For a new MSBT document, the MSBT ingest & MTU classify unit 280generates a new MSBT database record request and sends it to the MSBTdatabase 262, which creates the new record. For updated documents, theunit 280 generates an update an existing MSBT database record requestand sends it to the MSBT database 262. An example of an MSBT databaserecord is discussed in further detail with reference to FIG. 112 .

The unit 280 also MTU classifies each new MSBT document based on theextracted data. The MTU classification is one of: one or more specificMTUs, undecided/potential new MTU, or undecided.

The patent term recognition unit 290 and the patent annotating unit 292ingest patent documents (e.g., pending US patent applications, US issuedpatents, English translated pending foreign patent applications, andEnglish translated foreign issued patents). In an embodiment, the patentterm recognition unit 290 and the patent annotating unit 292 are acombined function performed by a co-processor of the improved computer.

The patent annotating unit 292 dissects (e.g., breaks down, analyzes) apatent document according to data of interest regarding MTUs in asimilar manner as an MSBT document. The unit 292 extracts data from thevarious portions of the patent document based on the type of section.For example, marketable feature data is extracted from portionssectioned as marketable feature, technical challenge data is extractedfrom portions sectioned as technical challenge, and so on.

For a new patent document, the unit 292 generates a new annotated patentdatabase record request and sends it to the annotated patent database268, which creates the new record. For an updated patent document (e.g.,issuance of a pending application, a foreign counterpart), the unit 292generates an update an existing annotated database record request andsends it to the annotated patent database 268. An example of anannotated patent database record is discussed in further detail withreference to FIG. 115 .

The unit 292 also MTU classifies each new annotated patent documentbased on the extracted data. The MTU classification is one of: one ormore specific MTUs, undecided/potential new MTU, or undecided.

The patent term recognition unit 290 analyzes a patent document toidentify patent terms. As used herein, a patent term is a claim term ora technical term. A claim term includes one or more words regarding aclaim noun (e.g., an element, a step, an input, output, and/or somequantifiable thing), a claim descriptor (e.g., a feature, a function, adescription, an interaction, an operational limitation of a claim nounand/or the like), and/or a claim relator (relationship of two or moreclaim nouns). A technical term includes one or more words that isregarding a technical aspect of an MTU.

For an identified patent term, the unit 290 determines, based onexisting records in the patent terms database 266, whether the patentterm is new or an existing one. For a new patent term, the unit 290generates a new patent term database record request and sends it to thepatent terms database 266. The record request includes the patent term,a technical summary of the term, a corresponding figure from the patentdocument, the type of term (e.g., claim term and/or technical term), andthe patent information of the patent document. The record request alsoincludes the MTU classification of the of the patent document.

For an existing patent term, the unit 290 generates an update patentterm database record request and sends it to the patent terms database266. The record update request includes the patent term, a technicalsummary of the term, a corresponding figure from the patent document,the type of term (e.g., claim term and/or technical term), and thepatent information of the patent document. The record update requestalso includes the MTU classification of the of the patent document. Inaddition, the patent term database updates a composite summary of thepatent term. An example of a patent term database record is discussed ingreater detail with reference to FIG. 116 .

The MTU identify, create, and data populate unit 282 routinely retrievesnewly added records from the MSBT database 262, the patent termsdatabase 262, and the annotated patents databased 268 to determine if anew MTU has emerged, and, if so, to request the creation of a new MTUdatabase record, and to update existing MTU records with new data. Theoperations of unit 282 will be described in greater detail withreference to FIGS. 117, 118 , and 123-136.

The MTU correlation unit 286 coordinates the MTU classifying of the MSBTdocuments, of patent documents, and of patent terms. The operations ofunit 286 will be described in greater detail with reference to one ormore of FIGS. 111, 114, 123, 137-139D.

The MTU cataloging unit 284 catalogs MTUs into technology maps and tiesMTUs to inclusion MTUs (e.g., higher tier MTUs), to composition MTUs(e.g., lower tier MTUs), and to related MTUs (e.g., MTUs on the sametier and in a similar MTU inclusion mapping). The operations of unit 284will be described in greater detail with reference to one or more ofFIGS. 148-150C.

FIG. 110 is a schematic block diagram of an example of characteristicsof MSBT (marketing, sales, business, & technology) document that isingested by the improved computer for technology. An MSBT document has adocument data type, a document format type, and a document source type.As an example, but not as an exhaustive example, the document data typesinclude financial data, business data, marketing data, sales data,technology data, and market data.

As an example, but not as an exhaustive example, the document formattype includes an article (newspaper, magazine, journal, etc.), a report,a study, a product review, a service review, a data sheet, a softwaredevelopment kit (SDK), sales material, marketing material, and a productdevelopment kit (PDK).

As an example, but not as an exhaustive example, the document sourcetype includes business, government, academia, journal, and dataanalytics. The document sources typically publish documents (i.e., makepublicly available) based on a particular agenda. For example, abusiness publishes documents based on the agenda of revenue generationand/or brand building. A government agency publishes documents based onthe agenda of public interest and/or public awareness. Academiapublishes documents based on the agenda of advance knowledge and brandbuilding. Technical journals publish documents based on the agenda ofadvancing knowledge, revenue generation, and brand building. Dataanalytics services publish documents based on the agenda of supportingknowledge advancement, revenue generation, and brand building.

The document data type, the document format, and the document sourcetype are used as weighting factors when data from a document is added toan MTU record and the influence the new data has on the understanding,definition, scope, composition, functioning, and/or use of an MTU. Forexample, a sales document will typically have a lower weightingregarding technical capabilities of a product/service than an academiaor technical journal article regarding the product/service.

FIG. 111 is a schematic block diagram of a further embodiment of anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology regardingingesting MSBT documents and creating MSBT database records. In thisembodiment, a co-processor 111 of the improved computer executes the MTUoperating system functions of MTU correlation, MTU error detect &management, MTU process management, and MTU system database management;the MSBT ingest & MTU classify unit (co-processor) 280 performs the MTUsystem applications of MSBT data identify & gather, MSBT data dissection& MTU interpret, and MSBT data record creation; and the MTU correlationunit (co-processor) 284 performs the MTU system application of MTUtagging of MSBT documents.

The unit 280 executes the MSBT data identify & gather system applicationto find MSBT documents. For example, the unit 280 generates a requestfor a particular MSBT document source to provide all of the newdocuments its published during a specified time frame. As anotherexample, the unit 280 generates a request for a particular MSBT documentsource to provide all documents its published regarding a particularsubject matter pertaining to an MTU. As a further example, the unit 280generates a request for a particular MSBT document source to findpublished documents regarding a particular subject matter pertaining toan MTU. As a still further example, the unit 280 generates a request formultiple MSBT document sources to provide all new documents they havepublished during a specified time frame and/or regarding a particularsubject matter pertaining to an MTU.

The unit 280 sends it requests for MSBT documents to the MSBT documentsources via the communication hardware of the improved computer. Thecomputing entity operating system functions of input/output managementand process management as executed by the co-processor 111 coordinateaccess to the network connections of the improved computer and ofsending the request to the MSBT document sources. The co-processor 111also executes the MTU process management OS function and the MTU errordetect & management OS function to coordinate management of MTUprocesses in conjunction with managing the computing entity processesand to ensure, if errors are detected, they are appropriately managed atthe MTU OS level and at the computing entity OS level.

The communication hardware of the improved computer receives found MSBTdocuments and sends them to the MSBT ingest & MTU classify unit 280executing the MSBT data identify & gather MTU system application. Theco-processor 111 executes the appropriate MTU operating system functionsand/or computing entity operating system functions to coordinate theconveyance of the received documents from the communication hardware tothe unit 280.

For an MSBT document received by the unit 280, it executes the MSBT datadissection & MTU interpret MTU system application to extract MTUorientated data (e.g., data corresponding to an MTU database record)from the document. The unit 280 sends the extracted MTU orientated data(and may further send the document) to the MTU correlation unit 286 forMTU classification.

The MTU correlation unit 286 executes the MTU tagging of MSBT documentsMTU system application based on the extracted data (and further on thedocument). As part of executing the MTU tagging application, the MTUcorrelation unit determines a technology category for the document andthe further determines, if possible, one or more technology maps of thetechnology category to which the document may pertain. To facilitatethis determination, the unit 286 retrieves MTU database records from theMTU database 264, which is coordinate through the MTU system databasemanagement OS function executed by co-processor 111.

Based on the retrieved MTU data, the unit 286 classifies the MSBTdocument. The MTU classifications include the name of one or more MTUs,undecided/potential new MTU, or undecided. The unit 286 provides the MTUclassification to the unit 280.

The unit 280 then executes the MSBT data record creation MTU systemapplication to generate a request for creating a new MSBT databaserecord. The unit 280 sends the request to the MSBT database 262 via theco-processor 111 that is executing the MTU system DB management OSfunction. In response to the request, the MSBT database 262 generates anew record of the newly ingested MSBT document. Note that theco-processor 111 executes the appropriate MTU operating system functionsand/or computing entity operating system functions to coordinate theexecution of the various processes of the MTU systems applications bythe unit 280 and/or by the unit 286.

FIG. 112 is a schematic block diagram of an example of a userinteractive graphical MSBT (marketing, sales, business, & technology)database record 570 of an MSBT database of the improved computer fortechnology. Each MSBT document stored by the MSBT database has its ownrecord. The record 570 includes an MSBT name section, an MTU classify(tag) section, a data section, a technical discussion section, and animage/diagram section.

The MSBT name section includes fields for the name of the MSBT document,the data type of the document (e.g., from FIG. 110 ), the documentauthor, the document format (e.g., from FIG. 110 ), the document sourcetype (e.g., from FIG. 110 ), and the document source name. The namesection may further include fields for publication date, published by,revision number, and/or other descriptive information.

The MTU classify (tag) section includes a check box for “undecided”, acheck box for “MTU classified” and a plurality of fields for the MTUnames for which the document is relevant; and a check box for“undecided/potential new MTU” and a plurality of fields for potentialnew MTU names.

The data section includes fields for a copy of the document (which couldinclude highlighting of the partition of the document into MTUsections), a general description of the document, metadata regarding thedocument, science categories, product/service data, manufacturing data,market impact data, and MTU technical boundaries data. The MTU technicalboundaries data includes fields for unique value propositions (UVPs),marketable features, technical challenges, problems, inventive concepts,solutions, inventive embodiments, patents (e.g., as mentioned in thedocument), standards (e.g., as mentioned in the document), and protocols(e.g., as mentioned in the document).

The technical discussion section includes a field for a summarydiscussion of technical subject matter disclosed in the document. Such adiscussion, if any, would be in accordance with a patent applicationstyle of discussing a background technology to provide a generalunderstanding of the technical subject matter and should be a paragraphor two in length. This discussion section is different from the generaldescription of the document, which is an overview discussion of thedocument (e.g., a data sheet for a product XYZ that lists features ABC).

The image/diagram section includes one or more diagrams to support thetechnical discussion. The image and/or diagram is extracted from thedocument and/or created to support the technical discussion.

FIG. 113 is a schematic block diagram of an example of characteristicsof patent documents ingested by the improved computer for technology. Apatent document is of an application type, has a status, and has beenfiled in one or more countries. As an example, but not as an exhaustiveexample, the application type includes provisional, non-provisionalutility, continuation, continuation-in-part, divisional, and PCT; thestatus includes pending, issued, and expired; and the country lists thecounty in which the particular patent document was filed.

FIG. 114 is a schematic block diagram of a further embodiment of anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology regardingingesting patent documents, creating annotated patent database records,and patent term database records. In this embodiment, a co-processor 111of the improved computer executes the MTU operating system functions ofMTU correlation, MTU error detect & management, MTU process management,and MTU system database management; the patent annotating and termrecognition units 290 and 292 execute the MTU system applications ofpatent data identify & gather, patent data dissection & MTU interpret,patent term identify and catalog, annotated patent database recordcreation, and patent term database record creation.

The units 290 and 292 executes the patent data identify & gather systemapplication to find patent documents. For example, the unit 290/292generates a request for a particular patent document source (e.g.,patent database service) to provide all of the new patent documents itspublished during a specified time frame. As another example, the unit290/292 generates a request for a particular patent document source toprovide all patent documents its published regarding a particularsubject matter pertaining to an MTU. As a further example, the unit290/292 generates a request for a particular patent document source tofind published patent documents regarding a particular subject matterpertaining to an MTU. As a still further example, the unit 290/292generates a request for multiple patent document sources to provide allnew patent documents they've published during a specified time frameand/or regarding a particular subject matter pertaining to an MTU. As ayet further example, the unit 290/292 routinely downloads publishedpatent applications and issued patent from one or more patent offices(e.g., the U.S. Patent and trademark office), which functions as thepatent document source.

The unit 290/292 sends it requests for patent documents to the MSBTdocument sources via the communication hardware of the improvedcomputer. The computing entity operating system functions ofinput/output management and process management as executed by theco-processor 111 coordinate access to the network connections of theimproved computer and of sending the request to the MSBT documentsources. The co-processor 111 also executes the MTU process managementOS function and the MTU error detect & management OS function tocoordinate management of MTU processes in conjunction with managing thecomputing entity processes and to ensure, if errors are detected, theyare appropriately managed at the MTU OS level and at the computingentity OS level.

The communication hardware of the improved computer receives foundpatent documents and sends them to the unit 290/292 executing the patentdata identify & gather MTU system application. The co-processor 111executes the appropriate MTU operating system functions and/or computingentity operating system functions to coordinate the conveyance of thereceived patent documents from the communication hardware to the unit290/292.

For a patent document received by the unit 290/292, it executes thepatent data dissection & MTU interpret MTU system application toidentifies MTU orientated data (e.g., data corresponding to an MTUdatabase record) in the patent document and to annotate the patentdocument in light of the MTU orientated data (e.g., highlight sectionsof the data document regarding benefits of the invention, problemaddressed by the invention, etc.). The unit 290/292 sends the extractedMTU orientated data (and may further send the annotated patent document)to the MTU correlation unit 286 for MTU classification.

The MTU correlation unit 286 executes the MTU tagging of MSBT documentsMTU system application based on the extracted data (and further on theannotated patent document). As part of executing the MTU taggingapplication, the MTU correlation unit determines a technology categoryfor the document and the further determines, if possible, one or moretechnology maps of the technology category to which the annotated patentdocument may pertain. To facilitate this determination, the unit 284retrieves MTU database records from the MTU database 264, which iscoordinate through the MTU system database management OS functionexecuted by co-processor 111.

Based on the retrieved MTU data, the unit 286 classifies the annotatedpatent document. The MTU classifications include the name of one or moreMTUs, undecided/potential new MTU, or undecided. The unit 286 providesthe MTU classification to the unit 290/292.

The unit 290/292 then executes the annotated patent database recordcreation MTU system application to generate a request for creating a newannotated patent database record. The unit 290/292 sends the request tothe annotated patent database 268 via the co-processor 111 that isexecuting the MTU system DB management OS function. In response to therequest, the annotated patent database 268 generates a new record of thenewly ingested annotated patent document.

The unit 290/292 also extracts patent terms from a received patentdocument via the patent term identify & catalog MTU system application.The unit 290/292 uses the MTU classification of the correspondingannotated patent document to MTU classify the patent term.

The unit 290/292 then executes the patent term database record creationMTU system application to generate a request for creating a new patentterm database record. The unit 290/292 sends the request to the patentterm database 266 via the co-processor 111 that is executing the MTUsystem DB management OS function. In response to the request, the patentterm database 266 generates a new record of the new patent term. Notethat the co-processor 111 executes the appropriate MTU operating systemfunctions and/or computing entity operating system functions tocoordinate the execution of the various processes of the MTU systemsapplications by the unit 290/292 and/or by the unit 286.

FIG. 115 is a schematic block diagram of an example of a userinteractive graphical annotated patent database record 572 of anannotated patent database of the improved computer for technology. Eachannotated patent document stored by the annotated patent database hasits own record. The record 572 includes a patent information section, anMTU classify (tag) section, a data section, a technical discussionsection, an image/diagram section, and a foreign counterpart section.

The patent information section includes fields for issued patent number,patent application type, patent application serial number (S/N), apublication number, a publication data, a filing date, a country inwhich the patent application was filed, patent owner information (e.g.,applicant, assignee, etc.), an issuance date, an expiration date, and apatent title.

The MTU classify (tag) section includes a check box for “undecided”, acheck box for “MTU classified” and a plurality of fields for the MTUnames for which the document is relevant; and a check box for“undecided/potential new MTU” and a plurality of fields for potentialnew MTU names.

The data section includes fields for a copy of the annotated patentdocument, metadata regarding the patent document, science categories,product/service data, manufacturing data, market impact data, and MTUtechnical boundaries data. The MTU technical boundaries data includesfields for unique value propositions (UVPs), marketable features,technical challenges, problems, inventive concepts, solutions, inventiveembodiments, patents (e.g., as mentioned in the document), standards(e.g., as mentioned in the document), and protocols (e.g., as mentionedin the document).

The technical discussion section includes a field for a summarydiscussion of technical subject matter disclosed in the patent document.Such a discussion, if any, would be in accordance with a patentapplication style of discussing a background technology to provide ageneral understanding of the technical subject matter and should be aparagraph or two to a page or two in length.

The image/diagram section includes one or more diagrams to support thetechnical discussion. The image and/or diagram is extracted from theannotated patent document and/or created to support the technicaldiscussion.

The foreign counterpart section includes fields for foreign counterpartsof the present patent document. The fields include issued patent number,patent application serial number, country, filing date, issuance date,and/or other fields comparable to the patent information section. Notethat if there is no data for a particular field, the field is leftblank. This is a general rule for records within any of the systemdatabases.

FIG. 116 is a schematic block diagram of an example of a userinteractive graphical patent term record 574 of a patent term databaseof the improved computer for technology. Each patent term stored by thepatent term database has its own record. The record 574 includes apatent term information section, an MTU classify (tag) section, atechnical discussion section, a synonym section, a related term section,and a patent term use section.

The patent term information section includes fields for the patent term,the quantity of its use (e.g., the number of patents that include thepatent term), the date of first use of the patent term, a summary of thehistorical use of the patent term and/or it evolution, and the date ofmost recent use. This allows the improved computer to determine thesignificance of the patent term and its trend (e.g., being used more,being used less, is new, is obsolete).

The MTU classify (tag) section includes a check box for “undecided”, acheck box for “MTU classified” and a plurality of fields for the MTUnames for which the document is relevant; and a check box for“undecided/potential new MTU” and a plurality of fields for potentialnew MTU names.

The technical discussion section includes a field for a summarydiscussion of patent term. Such a discussion should be in accordancewith a patent application style of discussing a background technology toprovide a general understanding of the technical subject matter and/or ageneral meaning. The summary should be a paragraph or two in length.

The synonym section includes fields for a list of synonyms of the patentterm. For example, the patent term of “processing circuit” has synonymsof “processor circuit”, “processing module”, “processing unit”,“processor unit”, and “processor”.

The related term section includes fields for a list of related patentterms to the present patent term. For example, the patent term of“processing circuit” has related patent terms of “central processingunit′, “microprocessor, and “microcontroller”.

The patent term use section includes fields for a list of patentdocuments that include the patent term. For each patent document, thereare fields for patent number, patent serial number, and country (morefields regarding the patents may be included).

FIG. 117 is a schematic block diagram of a further embodiment of anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology regarding theidentification of new MTUs, the creation of new MTU database records,and data populating existing MTU database records. For these functions,the improved computer includes the co-processor 111, the MTU identify,create, & data populate unit (co-processor) 282, the annotated patentdatabase 268, the patent terms database 266, the MTU database 264, andthe MSBT database 262.

The co-processor 111 executes the MTU operating system functions and/orthe computing entity operating system functions that support the MTUsystem applications of new MTU identification, update an MSBT databaserecord, update an annotated patent database record, update a patent termdatabase record, and create a new MTU database record. The MTU identify,create, & data populate unit 282 executes the listed MTU systemapplications.

The unit 282 executes the new MTU identification system application,which includes two main programs. The first is for records that have acurrent MTU classification of undecided and the second is for recordsthat have a current MTU classification of undecided/potential new MTU.The unit 282 executes the undecided program to retrieve undecided MSBTrecords, undecided annotated patent records, and undecided patent termrecords from the respective databases 262, 266, and 268. Theco-processor executes the MTU system database management OS function,the MTU process management OS function, the MTU error detect & manage OSfunction, the computing entity operating system (CE OS) processingmanagement function, the CE OS secondary memory management, the CE OSmain memory management, and/or the CE OS error detect & management tofacilitating the requesting and retrieving of records from therespective databases.

The unit 282 interprets the undecided records to determine whether thereis now sufficient data to change the MTU classification from undecidedto undecided/potential new MTU or to a new MTU. As further discussed ingreater detail with reference to one or more subsequent figures, theunit 282 analyzes the data of the undecided records in light of datarequirements for an MTU (i.e., the data contained in an MTU databaserecord).

In general, the unit 282 determines, for a sub-section of the datasection of an MTU database record, whether the sub-section hassufficient data to establish a definitive parameter for quantifying anemerging technology into an MTU. For example, the unit 282 determineswhether the collective undecided records provide sufficient informationto identify a unique value proposition, which is a definitive MTUboundary parameter. As another example, the unit 282 determines whetherthe collective undecided records provide sufficient information togenerate a reliable technical summary, which forms another parameter forquantifying an emerging technology. As a further example, the unit 282determines whether the collective undecided records provide sufficientinformation to identify a technology challenge, which is anotherdefinitive MTU boundary parameter.

For a parameter to quantify a technology as an MTU, the unit 282 assignsa value in a range of values based on the sufficiency (e.g., quantity,reliability, detail, etc.) of the information and on the unit's 282ability to determine that the information establishes a definitiveparameter. The unit 282 interprets the values for the parameters toquantify a technology as an MTU. If the interpretation of the values isinconclusive (e.g., not enough information to identify a potentially newMTU), the unit 282 maintains the “undecided” MTU classification for therecords.

If the interpretation of the values is conclusive (e.g., there is enoughinformation to clearly identify a new MTU), the unit 282 initiates thecreation of a new MTU record and changes the MTU classification for therecords to the name of the new MTU. If the interpretation of the valuesis between inconclusive and conclusive (e.g., enough information toindicated that there might be a new MTU, but not enough information toclearly establish a new MTU), the unit 282 creates a potential new MTUname and changes the MTU classification for the records to the“undecided/potential new MTU” with the name of the potentially new MTU.

For an MTU classification change (to undecided/potential new MTU or to anew MTU), the unit 282 executes the MTU system applications of updateMSBT database records, update annotated patent database records, andupdate patent term database records. Via these applications, the unit282 generates update requests and sends them to the respective databasesto update the MTU classification.

For a new MTU, the unit 282 executes the MTU system application ofcreate a new MTU database record. Via this application, the unit 282generates a new MTU database record request and sends it to the MTUdatabase 264, which creates the new MTU database record.

The unit 282 also executes the undecided/potential new MTU program toretrieve records (MSBT, annotated patents, and patent terms) having theMTU classification from the respective databases 262, 266, and 268. Theco-processor 111 executes the MTU system database management OSfunction, the MTU process management OS function, the MTU error detect &manage OS function, the computing entity operating system (CE OS)processing management function, the CE OS secondary memory management,the CE OS main memory management, and/or the CE OS error detect &management to facilitating the requesting and retrieving of records fromthe respective databases.

The undecided/potential new MTU program is similar to the undecidedprogram in that the unit 282 generates and interprets values for theparameters to quantify a technology as an MTU, with a difference beingthat the present retrieved data is for a specific potentially new MTU.If the interpretation of the values is conclusive (e.g., there is enoughinformation to clearly identify the new MTU), the unit 282 initiates thecreation of a new MTU record and changes the MTU classification for therecords to the name of the new MTU.

If the interpretation of the values remains less than conclusive, theunit 282 maintains the MTU classification for the records as“undecided/potential new MTU”. If the interpretation of the values hasnow become inconclusive (e.g., not enough information to identify apotentially new MTU), the unit 282 changes the MTU classification from“undecided/potential new MTU” to “undecided”. Note that the unit 282 mayexecute these MTU system applications concurrently and/or subsequentlywith the MSBT ingest & MTU classify unit 280, the patent termrecognition unit 290, and/or the patent annotating unit 292 executingtheir respective MTU system applications.

FIG. 118 is a schematic block diagram of a further embodiment of anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology regarding datapopulating existing MTU database records. For this function, the MTUidentify, create, and data populate unit 282 executes the MTU systemapplication regarding data populating. The unit also executes the MTUsystem applications of update and MSBT database record, update anannotated patent database record, update a patent database record,and/or update an MTU database record.

The co-processor 111 executes the MTU operating system functions and/orthe computing entity operating system functions that support the unitexecuting the above-mentioned MTU system applications and for writing toand/or reading from one or more of the system databases.

For an MTU database record, the unit 282 retrieves new database records(MSBT, annotated patent, and/or patent term) that have an MTUclassification of the MTU name of the present MTU from the respectivedatabases 262, 266, and 268. Via the MTU data populating systemapplication, the unit 282 extracts new information to add to the MTUdatabase record. Via the update an MTU record system application, theunit 282 generates a request to update the MTU database record with theextracted new information.

As the unit 282 determines the updates for the MTU database record, itdetermines, via the MTU data populating system application, whether theupdated MTU database record causes a change in the data an MSBT databaserecord, an annotated patent database record, and/or a patent termdatabase record. For example, if the updated data prompts an update tothe MTU name (e.g., changing from “processor circuit” to “processingcircuit” since most reference refer to the MTU as a processing circuit),the unit 282 generates database update requests for each effectedrecords and send the requests to the appropriate databases.

Note that the unit 282 may execute this MTU system applicationconcurrently and/or subsequently with the MSBT ingest & MTU classifyunit 280, the patent term recognition unit 290, and/or the patentannotating unit 292 executing their respective MTU system applications.Further note that the unit may execute this MTU system applicationconcurrently and/or subsequently with it executing the MTU systemapplication discussed in FIG. 117 .

FIG. 119 is a schematic block diagram of a further embodiment of anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology regarding thecataloging of MTUs into one or more technical maps. For this function ofthe improved computer, it utilizes the co-processor 111, the MTUcataloging unit 284, the MTU identify, create, and data populate unit282, the MSBT database 262, the MTU database 264, the patent termsdatabase 266, and the annotated patents database 268.

The MTU cataloging unit (co-processor) 284 executes the MTU systemapplications of MTU inclusion mapping, MTU includes diagram generation,MTU inclusion technical discussion generation, MTU composition mapping,MTU composition diagram generation, and MTU composition technicaldiscussion generation. The MTU identify, create, and data populate unitexecutes the MTU system application of update an MTU database record.

The co-processor 111 executes the MTU operating system functions and/orthe computing entity operating system functions that support the unitexecuting the above-mentioned MTU system applications and for writing toand/or reading from one or more of the system databases.

The unit 284 retrieves one or more MTU records, one or more MSBT recordsthat are MTU classified with the names of the one or more MTU records,one or more annotated patent records that are MTU classified with thenames of the one or more MTU records, and one or more patent termrecords that are MTU classified with the names of the one or more MTUrecords from the respective databases. For example, the unit 284retrieves the MTU record of touch screen controller and the supportingMSBT document records, the supporting annotated patent records, and/orthe supporting patent terms.

For a new MTU record, the executes the MTU inclusion mapping and MTUcomposition system applications by identifying one or relevanttechnology maps based on the data of the MTU database records and/or thedata of the supporting documents. Assume that this is the firstoccurrence of a touch screen controller in the literature (e.g., whichincludes the supporting documents) and is a new technology for the newtechnology of a touchscreen display.

The literature indicates that a touch screen display is a new userinput/output device for a cell phone. From this information, the unit284 retrieves the technology map that includes input/output devices of acell phone and may further retrieve other technology maps that includeinput/output devices.

Executing the MTU inclusion mapping system application, the unit 284determines that the touch screen controller MTU is included in the newtouch screen display MTU of the input/output devices MTU of a cell phoneMTU. Accordingly, the unit updates the technology map to include thetouch screen display MTU and the touch screen controller MTU.

Executing the MTU composition mapping system application, the unit 284determines that the touch screen controller MTU includes a pluralitysensor circuits and a touch processing circuit. The unit updates thetechnology map to include the sensor circuits and the touch processingcircuit.

Based on the updated technology map, the unit 284 executes the systemapplications of MTU inclusion diagram generation and MTU compositiondiagram generation to generate an MTU inclusion functional diagram, anMTU inclusion hierarchy diagram, an MTU composition functional diagram,and/or an MTU composition hierarchy diagram.

From the functional diagrams, the unit 284 executes the systemapplications of MTU inclusion technical discussion generation and MTUcomposition technical discussion generation. For example, the unit 284generates an MTU inclusion technical discussion based on the MTUinclusion functional diagram. As another example, the unit 284 generatesan MTU composition technical discussion based on the MTU compositionfunctional diagram.

The unit 284 provides the MTU inclusion functional diagram, the MTUinclusion hierarchy diagram, the MTU composition functional diagram, theMTU composition hierarchy diagram, the MTU inclusion technicaldiscussion, and/or the MTU composition technical discussion to the unit282. The unit 282 generates an MTU database update request for the touchscreen controller MTU to update the record to include the MTU inclusionfunctional diagram, the MTU inclusion hierarchy diagram, the MTUcomposition functional diagram, the MTU composition hierarchy diagram,the MTU inclusion technical discussion, and/or the MTU compositiontechnical discussion.

For an existing MTU database record that already includes the MTUinclusion functional diagram, the MTU inclusion hierarchy diagram, theMTU composition functional diagram, the MTU composition hierarchydiagram, the MTU inclusion technical discussion, and/or the MTUcomposition technical discussion, the unit 284 may update one or more ofthese data based on newly received documents.

The unit 284 retrieves newly added records that are MTU classified withthe names of the one or more MTU records of interest, and one or morepatent term records that are MTU classified with the names of the one ormore MTU records from the respective databases. For example, the unitretrieves newly added database records that are classified with thetouch screen controller MTU.

The unit 284 analyses the newly added documents to determine if thereare new features, functions, technical challenges, implementations, etc.with respect to the touch screen controller presently stored in thetouch screen controller MTU database record. If the unit identifieschanges, it determines whether the changes warrant an update to one ormore of the diagrams and/or to one or more of the technicaldescriptions. If not, the unit 284 concludes the analysis with noupdates to the diagrams and/or technical description.

If, however, the unit 284 determines that one or more changes warrant anupdate to the diagrams, the unit evokes diagram MTU systemapplication(s) to update the MTU inclusion functional diagram, the MTUinclusion hierarchy diagram, the MTU composition functional diagram,and/or the MTU composition hierarchy diagram. The unit then evokes theMTU system application(s) to update the, the MTU inclusion technicaldiscussion, and/or the MTU composition technical discussion.

FIG. 120 is a schematic block diagram of an embodiment of a portion ofthe improved computer regarding a subscription based user interface,subscription pricing calculations, and market impact of an MTU. Theportion of the improved computer includes the computing entity operationsystem 104, the MTU operating system 106, some of the system databases74, co-processors of the hardware section, the communication interfacehardware, and a plurality of MTU system applications 470. The systemdatabases includes the MSBT database 262, the MTU database 264, and themarket impact database 274.

The MTU system applications 470 includes a subscription based userinterface, subscription pricing, and market tech unit (MTU) marketimpact calculations. The MTU operating system 106 functions include theMTU correlation, the MTU processing management, the MTU system databasemanagement, the MTU error detection and management, the MTU securitymanagement, the MTU content management, and the user interfacemanagement.

The co-processors include a subscription pricing unit 107, asubscription based user interface unit 105, a market impact unit 288,and the MTU correlation unit 286. The communication hardware connectsthe improved computer to one or more networks (e.g., Internet, WAN, LAN,WLAN, cellular, etc.) through which an authorized and authenticated userdevice accesses one or more MTU user applications.

The subscription based user interface unit 105 executes the subscriptionbased user interface MTU system application to ensure that onlyauthorized and authenticated user device's access an MTU userapplication for subscribed to MTUs. The MTU user applications includeMTU generation and phase report, MTU existing patent data report, MTUexisting market impact report, MTU existing patent protection report,MTU previous and current value report, MTU future patent data report,MTU future market impact report, MTU future patent protection report,MTU future value report, MTU technology expansion report, MTU marketopportunity report, MTU expansion report, MTU patent protection expense& growth report, MTU architectural patent protection plan, MTU inventionidentification & claim drafting, MTU patent application drafting, MTUpatent prosecution drafting, MTU patent quality reports, MTU patentprotection plan execution tracking report, MTU constructive noticereport, MTU patent sale opportunity report, MTU patent purchaseopportunity report, MTU patent licensing opportunity report, MTU patentstandards report, and MTU patent spin-off or joint venture (JV)opportunity report.

The subscription pricing unit 107 executes the subscription pricing MTUsystem application. The pricing is based on an MTU access fee component,an access frequency component, and an MTU user application component.The MTU access fee component includes pricing plateaus based on thenumber of MTUs to be accessed. For example, there is a first feecomponent to have access to all MTUs, there is a second fee component toaccess the MTUs of a particular technology category (e.g., communicationtechnology), there is a third fee component to access MTUs of aparticular technology map, and there is a fourth fee component to accessan individual MTU, wherein the first fee component is greater than thesecond fee component, which is greater than the third fee component,which is greater than the fourth fee component. There is an MTU feepremium for proprietary MTUs (e.g., only available to client paying tokeep it proprietary).

The MTU user application fee component includes pricing plateaus basedon the number of MTU user applications to be accessed. For example,there is a first fee component to have access to all MTU userapplications, there is a second fee component to access the MTU userapplications of a particular analysis perspective (e.g., existing TMPIV,future TMPIV, TMPIV portfolio development, patent preparation &prosecution, patent exploitation), and there is a third fee component toaccess an individual MTU user application, wherein the first feecomponent is greater than the second fee component, which is greaterthan the third fee component.

The MTU access frequency fee component includes pricing plateaus basedon the frequency of accessing the improved computer for the chosen levelof MTUs and the chosen level of MTU user applications. For example,there is an annual fee component to have year-round access to theimproved computer, there is a monthly fee component to havemonth-by-month access to the improved computer, and there is a one-timeaccess fee component to access the improved computer once for the chosenlevel of MTUs and the chosen level of MTU user applications, wherein theannual fee component is greater than the monthly fee component, which isgreater than the one-time access fee component.

The subscription based user interface unit 105 records in a userdatabase (not shown) for storing user device information, a user devicesubscription selection regarding the MTU access fee component, theaccess frequency component, and the MTU user application component. Thesubscription based user interface unit 105 authentic using a variety oftechniques to ensure the user device is truly the user device and isbeing used by an authentic user. The subscription based user interfaceunit 105 authorizes an authenticated user device based on an inputtedservice request and the user device's stored subscription selections. Ifthe inputted service request is in accordance with the user device'sstored subscription selections, the subscription based user interfaceunit 105 allows access to fulfill the inputted service request.

If the inputted service request is not in accordance with the userdevice's stored subscription selections, the subscription based userinterface unit 105 provides message indicating such. In addition, thesubscription based user interface unit 105 provides informationregarding the difference between the inputted service request and theuser device's stored subscription selections. The subscription baseduser interface unit 105 further provides an annual price difference, amonthly price difference, and/or a one-time price difference regardingthe difference between fees of the inputted service request versus thefees of the user device's stored subscription selections.

If the user device selects one of the pricing options, the subscriptionbased user interface unit 105 allows access to the inputted servicerequest after payment has cleared. This allows flexibility in accessingthe various MTU user applications and/or accessing various number ofMTUs with transparency in the fee structure.

The market impact unit 288 executes the MTU system application of MTUmarket impact calculations. This discussed in greater detail withreference to FIG. 121 .

FIG. 121 is a schematic block diagram of a further embodiment of aportion of an improved computer for technology regarding market impactfor an MTU. The portion of the improved computer includes the marketimpact unit 288, the co-processor 11, the MSBT database 262, the MTUdatabase 264, and the market impact database 274. The market impact unit288 executes the MTU system application regarding MTU market impactcalculations, which includes a patent & present component, a futureforecast component, and a market impact record creation component.

The co-processor 111 executes the MTU operating system functions and/orthe computing entity operating system functions that support the unitexecuting the above-mentioned MTU system applications and for writing toand/or reading from one or more of the system databases.

The unit 288 retrieves past and present (P&P) MSBT data and predictiveMSBT data from the MSBT database 266. The unit 288 also retrieves MTUdata from the MTU database 264. For an MTU, the unit 288 generatesmarket impact data, which is regarding the impact the MTU has had on themarket and the forecasted impact the MTU is likely to have on themarket.

If the market impact has previously been calculated for the MTU, theunit 288 generates a market impact database record update request toadds the latest calculations and their sources to the market impactdatabase 274. If this the first calculation of market impact for theMTU, the unit 288 generates a request for a new market impact databaserecord and sends it to the market impact database 274. The variouscalculations for market impact are discussed in greater detail withreference to one or more other Figures.

FIG. 122 is a schematic block diagram of an example of a userinteractive graphical database record 576 for market impact of an MTU ofa market impact (MI) database of the improved computer for technology.The record includes a market impact (MI) MTU name section, a past andpresent data section, a future forecast data section, a past and presentdiscussion section, a past and present diagram section, a futureforecast discussion section, and a future forecast diagram section.

The market impact (MI) MTU name section includes fields for the MTUname, the names of one or more MTU inclusion names, and the names of oneor more MTU composition names. The names of inclusion MTUs and/orcomposition MTUs are included if they are accessed to help determine themarket impact for the present MTU.

The past and present data section includes fields for a list of MSBTdatabase records use to determine the past and present market impact.This section also includes a field for metadata regarding the list.

The future forecast data section includes fields for a list of MSBTdatabase records use to determine the future forecasted market impact.This section also includes a field for metadata regarding the list.

The past and present discussion section includes fields for a past andpresent summary of the financial and market performance from an MTUinclusion perspective. This section also includes a field for a past andpresent summary of the financial and market performance from an MTUcomposition perspective.

The past and present diagram section includes fields for a past andpresent diagram(s) that support the summary of the financial and marketperformance from an MTU inclusion perspective. This section alsoincludes a field for a past and present diagram(s) that support thesummary of the financial and market performance from an MTU compositionperspective.

The future forecast discussion section includes fields for a futureforecasted summary of the financial and market performance from an MTUinclusion perspective. This section also includes a field for a futureforecasted summary of the financial and market performance from an MTUcomposition perspective.

The future forecast diagram section includes fields for a futureforecasted diagram(s) that support the summary of the financial andmarket performance from an MTU inclusion perspective. This section alsoincludes a field for a future forecasted diagram(s) that support thesummary of the financial and market performance from an MTU compositionperspective.

FIG. 123 is a schematic block diagram of a further embodiment of anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology regarding MSBTdocuments. In this Figure, the functional operations of the MSBT dataidentify & gather MTU system application, the MSBT data dissection & MTUinterpret MTU system application, the MTU tagging of an MSBT documentMTU system application, and MSBT database record create MTU systemapplication are discussed.

When the improved computer executes the MSBT data identify & gather MTUsystem application, it uses search criteria to find and vet potentiallyrelevant MSBT documents. The search criteria includes, but is notlimited to, known MTUs, known data sources, known data authors, knowproducts/services, known technical topics, potential new MTUs, new datasources, new data authors, new products/services, and/or new technicaltopics. For this MTU system application, known means that at least onerecord in at least one of the system databases has information regardingthe known search criteria. An example of searching for potentiallyrelevant MSBT documents will be discussed with reference to FIG. 124 .The vetting of potentially relevant MSBT documents will be discussedwith reference to FIG. 125 .

When the improved computer executes the MSBT data dissection & MTUinterpret MTU system application, it follows a basic flow chart ofidentifying information about the document, look for relevant MTUorientated data, apply an MSBT document filter function, create a patentstyle discussion of the document, and create metadata for the document.Information about the document includes document name (title, or otheridentifying phrase), the name of the documents author (e.g., a person),the name of the document source (e.g., publisher, company, etc.), thedocument data type (see FIG. 110 ), the document format (see FIG. 110 ),the document source type (see FIG. 110 ), whether this document is arepublication (i.e., the same document but republished by a seconddocument source), and whether this document is a new version or editionof a previously published document.

The MTU orientated data includes, but is not limited to, sciencecategory data, product/service data, function data, a descriptive image,market impact data, a technical boundary (e.g., unique valueproposition, marketable feature, technical challenge, problem, inventiveconcept, implementation element, implementation mechanism,implementation variant, solution, and/or inventive embodiment),manufacturing data, and/or a technical image.

The improved computer executes the MSBT document filter to determine,based on the information about the document and the identified MTUorientated data, the usability of document. In general, the improvedcomputer determines the usefulness of an MSBT document for identifyingnew MTUs and/or for further defining existing MTUs. An example of MSBTdocument filtering is discussed with reference to FIG. 131 .

The improved computer creates a patent style discussion of the documentif it has some measure of usability. As used herein, “a patent stylediscussion” refers to a written discussion, alone or with reference to afigure or diagram, that provides a sufficient level of detail so thatthe content and/or purpose of the document can be generally understoodfrom an MTU perspective, which should be achievable in a few paragraphsor less. Examples of such patent style discussions are presented withreference to several Figures; one particular example is discussed withreference to FIG. 129B.

The improved computer creates metadata for the document if it has somemeasure of usability. For example, the metadata includes, but is notlimited to, the date of first publication, the name of the firstpublishing entity, republication dates (if any), dates for olderversions and/or editions of the document, and/or names of the publishersof the older versions and/or editions. An example of metadata isdiscussed with reference to FIG. 130B.

The improved computer tags MSBT document as discussed with reference toFIGS. 137-139D and creates a request for new MSBT database record and/ora request for updating an existing MSBT database record as discussedwith reference to FIG. 141 .

FIG. 124 is a logic diagram of an example of a method for ingesting MSBTdocuments by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technology.The method begins at step 580 where the improved computer communicateswith known providers of MSBT documents regarding known topics (e.g.,existing and non-obsoleted MTUs). As shown, a known provider includes aknown data author, a known data source, and/or a known product/serviceprovider. A known topic includes a known MTUs and/or its synonyms, aknown technology topic, and/or a known product/service.

The communication is through the communication hardware of the improvedcomputer to access MSBT documents via one or more networks (e.g., WAN,LAN, internet, cellular, etc.). The communication can be done in avariety of ways. For example, the improved computer sends a query to aknown MSBT document source (e.g., a computing entity associated with aperson, company, or other legal entity that makes MSBT documentspublicly available) for new MSBT documents in general or with respect toa specified MTU or set of MTUs. As another example, the improvedcomputer routinely (e.g., periodically, pseudo randomly, when there is anew document, etc.) receives new MSBT documents in general or withrespect to a specific MTU or set of MTUs from a known source (e.g., asubscription with the known source to receive MSBT documents). As afurther example, the improved computer scans a website of a known sourcefor new MSBT documents (e.g., a company selling products/services, auniversity, etc.). As a still further example, the improved computerreviews internet postings by a known source of new MSBT documents.

The method continues at step 582, where the improved computer determineswhether it has received a new MSBT document from a known source. If yes,and for each document received from a known provider regarding a knowntopic, the method continues at step 584 where the improved computer vetsthe received document. An example of vetting an MSBT document isdiscussed with reference to FIG. 125 .

From step 584 and from a no response to step 582, the method continuesat step 586 where the improved computer communications with knownsources regarding new topics. As shown, the new topics includes, but arenot limited to, potential new MTUs, new products/services, newtechnology topics beyond existing MTUs, and/or technology discussionsregarding hypothesized scientific theories.

The method continues at step 588, where the improved computer determineswhether it has received a new MSBT document from a known sourceregarding a new topic. If yes, and for each document received from aknown provider regarding a new topic, the method continues at step 590where the improved computer vets the received document.

From step 590 and from a no response to step 588, the method continuesat step 592 where the improved computer determines whether it hasidentified a new provider. As shown, a new provider includes a new dataauthor, a new data source, and/or a new product/service provider. If anew provider is not identified, the method repeats at step 580.

If a new provider is identified, the method continues at step 594 wherethe improved computer communicates with the new provider regarding knowntopics. The method continues at step 596, where the improved computerdetermines whether it has received a new MSBT document from a new sourceregarding a known topic. If yes, and for each document received from anew provider regarding a known topic, the method continues at step 598where the improved computer vets the received document.

From step 598 and from a no response to step 596, the method continuesat step 600 where the improved computer communications with a newprovider regarding a new topic. The method continues at step 602, wherethe improved computer determines whether it has received a new MSBTdocument from a new source regarding a new topic. If yes, and for eachdocument received from a new provider regarding a new topic, the methodcontinues at step 604 where the improved computer vets the receiveddocument. If not, the method repeats at step 580.

The improved computer routinely executes the method of FIG. 124 . Forexample, the improved computer continually executes the method andreceives new MSBT documents 24 hours a day, 7 days a week. As anotherexample, the improved computer executes the method on an hourly basis ora daily basis, 7 days a week. As yet another example, the improvedcomputer executes the method with a different frequency for weekdaysversus weekends.

FIG. 125 is a logic diagram of another example of ingesting MSBTdocuments by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technologyregarding vetting of documents to establish confidence factors. Themethod begins at step 610 where the improved computer quarantines eachincoming document. The incoming documents are quarantined in separatehardware from the hardware of the improved computer and the software ofthe quarantined hardware is separate from the software of the improvedcomputer.

The method continues at step 612, where the quarantine hardware andsoftware scans the document for “bad actor” coding. As used herein, abad actor is a person or computer bot that operates with maliciousintent and does so via hack attempts, phishing attacks, denial ofservice attacks, bait and switch attacks, cookie theft, a virus, atrojan horse, a worm, click jacking attacks, keylogger attacks,eavesdropping, waterhole attacks, SQL injection attacks, DNS spoofingattacks, and/or any other forms for digital attacks.

The method continues at step 614, where the quarantine hardware andsoftware determines whether any “bad actor” coding was found. If yes,the method continues at step 616 where the quarantine hardware andsoftware deletes the document for quarantine and informs the improvedcomputer. The method continues at step 618 where the improved computerdetermines whether to seek the document from a different provider. Ifyes, the method continues at step 620 where the improved computerinitiates a search for the document for another provider. From step 620or a no response from step 618, the method continues at step 622 wherethe method repeats for the next document in quarantine.

If, at step 614, no “bad actor” coding was found, the method continuesat step 624 where the quarantine hardware and software determine whetherthe content of the document has been altered. The content of a documentmay be altered in a variety of ways. For example, the content wasaltered as a result of a data transmission error. As another example,the content was altered intentionally by a person or a computer bot. Ifthe content has been altered, the method repeats at step 616.

If the content has not been altered, the method continues at step 626where the quarantine hardware and software releases the document to theimproved computer and the improved computer determines whether theprovider of the document is a known provider. If yes, the methodcontinues at step 640 where the improved computer determines whetherprovider is reliable (which is based on a historical analysis ofdocuments provided by the provider). If not, the method continues atstep 642 where the improved computer sets a low confidence factor forthe document and the process repeats for another document.

If, at step 640, the provider is reliable, the method continues at step644 where the improved computer determines whether subject matter of thedocument is typical subject matter made publicly available by theprovider. If yes, the method continues at step 646 where the improvedcomputer sets a high confidence factor, and the method repeats for thenext document.

If not, the method continues at step 648 where the improved computerdetermines whether there is a general consensus on the subject andwhether the subject matter presented by the provider is in line with thegeneral consensus. In this instance, general consensus refers to asufficient amount of scientific data to support the validity orinvalidity of a hypothesized technical theory. If yes, the methodcontinues at step 650 where the improved computer sets a high confidencefactor, and the method repeats for the next document.

If not, the method continues at step 652 where the improved computersets the confidence factor based on a sliding scale. The sliding scaleis based on the amount of data available to validate or invalidate ahypothesized technical theory, the level of data in the present documentto validate or invalidate a hypothesized technical theory, and thedifference between the data of the present document than the availabledata.

If, at step 626, the provider is not a known provider (i.e., is a newprovider) the method continues at step 628 where the improved computerdetermines whether to trust the new provider. For example, the improvedcomputer gathers data regarding the new provider and the level ofreliability of documents it makes publicly available. If there issufficient data to support trusting the new provider, the new provideris trusted, if not, the new provider is not trusted (i.e., is treated asan unreliable provider). Note that the improved computer routinelyupdates the reliability score of a provider.

If the new provider is not yet trusted, the method continues at step642, where confidence factor is set to a low value. If the new provideris trusted, the method repeats at step 648.

FIG. 126 is a logic diagram of another example of a method of ingestingMSBT documents by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technologyregarding ingesting and dissecting an MSBT document. The method beginsat step 660 where the improved computer inputs an MSBT document. Themethod continues at step 662 where the improved computer determines theformat of the document. For example, but not as an exhaustive example,the document format includes one or more of an article (newspaper,magazine, journal, etc.), a report, a study, a product review, a servicereview, a data sheet, a software development kit (SDK), sales material,a white paper, a press release, marketing material, and a productdevelopment kit (PDK).

The method continues at step 664 where the improved computer scans thedocument in accordance with the document format type. As discussed withreference to FIG. 132 , scanning a document of a particular documentformat type may include specific scanning rules. In general, thescanning includes scanning one or more of text, symbols, images,diagrams, tables, charts, etc. so that the document can be partitionedinto section regarding MTU orientated data.

The method continues at step 666 where the improved computer identifiesterms, phrase, images, diagrams, and/or symbols. The method continues atstep 668 where the improved computer interprets the identified terms,phrase, images, diagrams, and/or symbols to partition the document intosections regarding MTU orientated data so that the improved can performsteps 670 through 686.

At step 670 the improved computer determines document information fromthe document. The document information includes a document name (title,or other identifying phrase), the name of the documents author (e.g., aperson), the name of the document source (e.g., publisher, company,etc.), the document data type (see FIG. 110 ), the document format (seeFIG. 110 ), the document source type (see FIG. 110 ), whether thisdocument is a republication (i.e., the same document but republished bya second document source), and whether this document is a new version oredition of a previously published document.

The method continues at step 672 where the improved computer thedetermines data regarding MTU subject matter, which includes sciencecategory data, manufacturing data, product/service data, market impactdata, MTU inclusion data, functional (e.g., technical) data, and/or MTUcomposition data. The method continues at step 674 where the improvedcomputer determines data regarding MTU technical boundaries. This dataincludes unique value proposition data, technical challenge data,solution data, marketable features data, problem data, and/or listedpatents and/or patent applications.

The method continues at step 676 where the improved computer generatesan MSBT name section summary for an MSBT database record based on thedocument information, the document format type, the document sourcetype, and/or the document data type. The method continues at step 678where the improved computer generates a brief description of the subjectmatter of the document.

The method continues at step 680 where the improved computer generates asummary for each of the MTU subject matter topic contained in thedocument. The method continues at step 682 where the improved computergenerates a summary for each MTU technical boundary topic contained inthe document.

The method continues at step 684 where the improved computer generates asummary of data elements of the document that was inclusive (e.g., wasnot align, correspond to, related to, etc.) an MTU tech boundary topicor other MTU topic. For example, a company's annual report includestechnical data, product/service data, financial data, sales data, etc.,which is relevant (e.g., fits) with MTU orientated data. The annualreport also includes information regarding securities compliance, legaldisclaimers, inventors specific information, etc. that is not directlyrelated to MTU orientated data. Such unrelated data, however, may beuseful in interpreting some relevant MTU orientated data.

FIGS. 127A through 127D are a logic diagram of another example ofingesting MSBT documents by an MSBTP (marketing, sales, business,technology, and patent) data gathering section of an improved computerfor technology that is regarding step 672 of FIG. 126 . The methodbegins at step 690 of FIG. 127A where the improved computer estimatescorrelated MTUs based on the content of the data and, in particular, thename section data. For example, the improved computer interprets theextracted data of the document (e.g., the partitions of data based onMTU orientated data) to identify one or more MTUs to which the documentis relevant or may be relevant.

The method continues at step 692 where the improved computer retrievesMTU orientated subject matter data from the database records of theestimated corelated MTUs. The MTU oriented data includes sciencecategory data, manufacturing data, product/service data, market impactdata, MTU inclusion data, MTU function data, and MTU composition data.The processing of MTU tech boundary data is discussed with reference toFIGS. 128A through 128C.

The method continues at step 694 where the improved computer comparesthe retrieved science category data from a correlated MTU with thescience category data of the document. The method continues at step 696where the improved computer determines whether the correlation ofscience category data of the document with the science category data ofthe MTU is above an upper threshold. If yes, the method continues atstep 698 where the improved computer definitively determines that thescience category data of the document correlates (relates to, is similarto, is the same as, etc.) with the science category data of the MTU.

If the answer to step 696 was no, the method continues at step 700 wherethe improved computer determines whether the correlation of sciencecategory data of the document with the science category data of the MTUis below a lower threshold. If yes, the method continues at step 702where the improved computer indicates that there is no science categorydata correlation.

If the answer to step 700 was no, the method continues at step 704 wherethe improved computer indicates that the correlation of science categorydata of the document with the science category data of the MTU isinconclusive. The method continues at step 706 where the improvedcomputer flags the science category data of the document for subsequentanalysis with respect to the MTU. Note that, as the MTU record continuesto add data, the added data may assisted in a subsequent analysis of thescience category data. Further note that FIGS. 137-139D provide examplesof correlating data of a document with data of an MTU.

From steps 698, 702, and 706, the method continues at step 708 where theimproved computer compares the retrieved manufacturing data from acorrelated MTU with the manufacturing data of the document. The methodcontinues at step 710 where the improved computer determines whether thecorrelation of manufacturing data of the document with the manufacturingdata of the MTU is above an upper threshold. If yes, the methodcontinues at step 712 where the improved computer definitivelydetermines that the manufacturing data of the document correlates(relates to, is similar to, is the same as, etc.) with the manufacturingdata of the MTU.

If the answer to step 710 was no, the method continues at step 714 wherethe improved computer determines whether the correlation ofmanufacturing data of the document with the manufacturing data of theMTU is below a lower threshold. If yes, the method continues at step 716where the improved computer indicates that there is no manufacturingdata correlation.

If the answer to step 714 was no, the method continues at step 718 wherethe improved computer indicates that the correlation of manufacturingdata of the document with the manufacturing data of the MTU isinconclusive. The method continues at step 720 where the improvedcomputer flags the manufacturing data of the document for subsequentanalysis with respect to the MTU. Note that, as the MTU record continuesto add data, the added data may assisted in a subsequent analysis of themanufacturing data.

From steps 712, 716, and 720, the method continues at step 722 of FIG.127B where the improved computer compares the retrieved product/servicedata from a correlated MTU with the product/service data of thedocument. The method continues at step 724 where the improved computerdetermines whether the correlation of product/service data of thedocument with the product/service data of the MTU is above an upperthreshold. If yes, the method continues at step 726 where the improvedcomputer definitively determines that the product/service data of thedocument correlates (relates to, is similar to, is the same as, etc.)with the product/service data of the MTU.

If the answer to step 724 was no, the method continues at step 728 wherethe improved computer determines whether the correlation ofproduct/service data of the document with the product/service data ofthe MTU is below a lower threshold. If yes, the method continues at step730 where the improved computer indicates that there is noproduct/service data correlation.

If the answer to step 728 was no, the method continues at step 732 wherethe improved computer indicates that the correlation of product/servicedata of the document with the product/service data of the MTU isinconclusive. The method continues at step 734 where the improvedcomputer flags the product/service data of the document for subsequentanalysis with respect to the MTU. Note that, as the MTU record continuesto add data, the added data may assist in a subsequent analysis of theproduct/service data.

From steps 726, 730, and 732, the method continues at step 736 where theimproved computer compares the retrieved market impact data from acorrelated MTU with the market impact data of the document. The methodcontinues at step 738 where the improved computer determines whether thecorrelation of market impact data of the document with the market impactdata of the MTU is above an upper threshold. If yes, the methodcontinues at step 740 where the improved computer definitivelydetermines that the market impact data of the document correlates(relates to, is similar to, is the same as, etc.) with the market impactdata of the MTU.

If the answer to step 738 was no, the method continues at step 742 wherethe improved computer determines whether the correlation of marketimpact data of the document with the market impact data of the MTU isbelow a lower threshold. If yes, the method continues at step 744 wherethe improved computer indicates that there is no market impact datacorrelation.

If the answer to step 742 was no, the method continues at step 746 wherethe improved computer indicates that the correlation of market impactdata of the document with the market impact data of the MTU isinconclusive. The method continues at step 748 where the improvedcomputer flags the market impact data of the document for subsequentanalysis with respect to the MTU. Note that, as the MTU record continuesto add data, the added data may assisted in a subsequent analysis of themarket impact data.

From steps 740, 744, and 748, the method continues at step 750 of FIG.127C where the improved computer compares the retrieved MTU inclusiondata from a correlated MTU with the MTU inclusion data of the document.The method continues at step 752 where the improved computer determineswhether the correlation of MTU inclusion data of the document with theMTU inclusion data of the MTU is above an upper threshold. If yes, themethod continues at step 754 where the improved computer definitivelydetermines that the MTU inclusion data of the document correlates(relates to, is similar to, is the same as, etc.) with the MTU inclusiondata of the MTU.

If the answer to step 752 was no, the method continues at step 756 wherethe improved computer determines whether the correlation of MTUinclusion data of the document with the MTU inclusion data of the MTU isbelow a lower threshold. If yes, the method continues at step 758 wherethe improved computer indicates that there is no MTU inclusion datacorrelation.

If the answer to step 756 was no, the method continues at step 760 wherethe improved computer indicates that the correlation of MTU inclusiondata of the document with the MTU inclusion data of the MTU isinconclusive. The method continues at step 762 where the improvedcomputer flags the MTU inclusion data of the document for subsequentanalysis with respect to the MTU. Note that, as the MTU record continuesto add data, the added data may assisted in a subsequent analysis of theMTU inclusion data.

From steps 754, 758, and 762, the method continues at step 764 where theimproved computer compares the retrieved MTU function data from acorrelated MTU with the MTU function data of the document. The methodcontinues at step 766 where the improved computer determines whether thecorrelation of MTU function data of the document with the MTU functiondata of the MTU is above an upper threshold. If yes, the methodcontinues at step 768 where the improved computer definitivelydetermines that the MTU function data of the document correlates(relates to, is similar to, is the same as, etc.) with the MTU functiondata of the MTU.

If the answer to step 766 was no, the method continues at step 770 wherethe improved computer determines whether the correlation of MTU functiondata of the document with the MTU function data of the MTU is below alower threshold. If yes, the method continues at step 772 where theimproved computer indicates that there is no MTU function datacorrelation.

If the answer to step 770 was no, the method continues at step 774 wherethe improved computer indicates that the correlation of MTU functiondata of the document with the MTU function data of the MTU isinconclusive. The method continues at step 776 where the improvedcomputer flags the MTU function data of the document for subsequentanalysis with respect to the MTU. Note that, as the MTU record continuesto add data, the added data may assist in a subsequent analysis of theMTU function data.

From steps 768, 772, and 776, the method continues at step 778 of FIG.127D where the improved computer compares the retrieved MTU compositiondata from a correlated MTU with the MTU composition data of thedocument. The method continues at step 780 where the improved computerdetermines whether the correlation of MTU composition data of thedocument with the MTU composition data of the MTU is above an upperthreshold. If yes, the method continues at step 782 where the improvedcomputer definitively determines that the MTU composition data of thedocument correlates (relates to, is similar to, is the same as, etc.)with the MTU composition data of the MTU.

If the answer to step 780 was no, the method continues at step 784 wherethe improved computer determines whether the correlation of MTUcomposition data of the document with the MTU composition data of theMTU is below a lower threshold. If yes, the method continues at step 786where the improved computer indicates that there is no MTU compositiondata correlation.

If the answer to step 784 was no, the method continues at step 788 wherethe improved computer indicates that the correlation of MTU compositiondata of the document with the MTU composition data of the MTU isinconclusive. The method continues at step 790 where the improvedcomputer flags the MTU composition data of the document for subsequentanalysis with respect to the MTU. Note that, as the MTU record continuesto add data, the added data may assisted in a subsequent analysis of theMTU composition data. The method continues steps 782, 786, and 790 atstep 674, which is discussed with reference to FIGS. 128A through 128C.

FIGS. 128A through 128C are a logic diagram of another example ofingesting MSBT documents by an MSBTP (marketing, sales, business,technology, and patent) data gathering section of an improved computerfor technology that is regarding step 674 of FIG. 126 . The methodbegins at step 800 of FIG. 128A where the improved computer estimatescorrelated MTUs based on the content of the data and, in particular, thename section data. For example, the improved computer interprets theextracted data of the document (e.g., the partitions of data based onMTU orientated data) to identify one or more MTUs to which the documentis relevant or may be relevant.

The method continues at step 802 where the improved computer retrievesMTU tech boundary data from the database records of the estimatedcorelated MTUs. The MTU tech boundary data includes unique valueproposition data, marketable features data, technology challenges data,inventive concept data, problem data, solution data, and/or patent data.

The method continues at step 804 where the improved computer comparesthe retrieved unique value proposition data (UVP) data from a correlatedMTU with the UVP data of the document. The method continues at step 806where the improved computer determines whether the correlation of UVPdata of the document with the UVP data of the MTU is above an upperthreshold. If yes, the method continues at step 808 where the improvedcomputer definitively determines that the UVP data of the documentcorrelates (relates to, is similar to, is the same as, etc.) with theUVP data of the MTU.

If the answer to step 806 was no, the method continues at step 810 wherethe improved computer determines whether the correlation of UVP data ofthe document with the UVP data of the MTU is below a lower threshold. Ifyes, the method continues at step 812 where the improved computerindicates that there is no UVP data correlation.

If the answer to step 810 was no, the method continues at step 814 wherethe improved computer indicates that the correlation of science categorydata of the document with the science category data of the MTU isinconclusive. The method continues at step 816 where the improvedcomputer flags the UVP data of the document for subsequent analysis withrespect to the MTU. Note that, as the MTU record continues to add data,the added data may assisted in a subsequent analysis of the UVP data.Further note that FIGS. 137-139D provide examples of correlating data ofa document with data of an MTU.

From steps 808, 812, and 816, the method continues at step 818 where theimproved computer compares the retrieved marketable feature data from acorrelated MTU with the marketable feature data of the document. Themethod continues at step 820 where the improved computer determineswhether the correlation of marketable feature data of the document withthe marketable feature data of the MTU is above an upper threshold. Ifyes, the method continues at step 822 where the improved computerdefinitively determines that the marketable feature data of the documentcorrelates (relates to, is similar to, is the same as, etc.) with themarketable feature data of the MTU.

If the answer to step 820 was no, the method continues at step 824 wherethe improved computer determines whether the correlation of marketablefeature data of the document with the marketable feature data of the MTUis below a lower threshold. If yes, the method continues at step 826where the improved computer indicates that there is no marketablefeature data correlation.

If the answer to step 824 was no, the method continues at step 828 wherethe improved computer indicates that the correlation of marketablefeature data of the document with the marketable feature data of the MTUis inconclusive. The method continues at step 830 where the improvedcomputer flags the marketable feature data of the document forsubsequent analysis with respect to the MTU. Note that, as the MTUrecord continues to add data, the added data may assisted in asubsequent analysis of the marketable feature data.

From steps 822, 826, and 830, the method continues at step 832 of FIG.128B where the improved computer compares the retrieved tech challengedata from a correlated MTU with the tech challenge data of the document.The method continues at step 834 where the improved computer determineswhether the correlation of tech challenge data of the document with thetech challenge data of the MTU is above an upper threshold. If yes, themethod continues at step 836 where the improved computer definitivelydetermines that the tech challenge data of the document correlates(relates to, is similar to, is the same as, etc.) with the techchallenge data of the MTU.

If the answer to step 834 was no, the method continues at step 838 wherethe improved computer determines whether the correlation of techchallenge data of the document with the tech challenge data of the MTUis below a lower threshold. If yes, the method continues at step 840where the improved computer indicates that there is no tech challengedata correlation.

If the answer to step 838 was no, the method continues at step 842 wherethe improved computer indicates that the correlation of tech challengedata of the document with the tech challenge data of the MTU isinconclusive. The method continues at step 844 where the improvedcomputer flags the tech challenge data of the document for subsequentanalysis with respect to the MTU. Note that, as the MTU record continuesto add data, the added data may assist in a subsequent analysis of thetech challenge data.

From steps 836, 840, and 844, the method continues at step 846 where theimproved computer compares the retrieved problem data from a correlatedMTU with the problem data of the document. The method continues at step848 where the improved computer determines whether the correlation ofproblem data of the document with the problem data of the MTU is abovean upper threshold. If yes, the method continues at step 850 where theimproved computer definitively determines that the problem data of thedocument correlates (relates to, is similar to, is the same as, etc.)with the problem data of the MTU.

If the answer to step 848 was no, the method continues at step 852 wherethe improved computer determines whether the correlation of problem dataof the document with the problem data of the MTU is below a lowerthreshold. If yes, the method continues at step 854 where the improvedcomputer indicates that there is no problem data correlation.

If the answer to step 852 was no, the method continues at step 856 wherethe improved computer indicates that the correlation of problem data ofthe document with the problem data of the MTU is inconclusive. Themethod continues at step 858 where the improved computer flags theproblem data of the document for subsequent analysis with respect to theMTU. Note that, as the MTU record continues to add data, the added datamay assisted in a subsequent analysis of the problem data. Note problemdata may further include inventive concept data, implementation elementsdata, implementation mechanisms data, and/or implementation variantsdata.

From steps 850, 854, and 858, the method continues at step 860 of FIG.128C where the improved computer compares the retrieved solution datafrom a correlated MTU with the solution data of the document. The methodcontinues at step 862 where the improved computer determines whether thecorrelation of solution data of the document with the solution data ofthe MTU is above an upper threshold. If yes, the method continues atstep 864 where the improved computer definitively determines that thesolution data of the document correlates (relates to, is similar to, isthe same as, etc.) with the solution data of the MTU.

If the answer to step 862 was no, the method continues at step 866 wherethe improved computer determines whether the correlation of solutiondata of the document with the solution data of the MTU is below a lowerthreshold. If yes, the method continues at step 868 where the improvedcomputer indicates that there is no solution data correlation.

If the answer to step 866 was no, the method continues at step 870 wherethe improved computer indicates that the correlation of solution data ofthe document with the solution data of the MTU is inconclusive. Themethod continues at step 872 where the improved computer flags thesolution data of the document for subsequent analysis with respect tothe MTU. Note that, as the MTU record continues to add data, the addeddata may assisted in a subsequent analysis of the solution data. Notethat the solution data may further include novelty nugget data and/orinventive embodiment data.

From steps 864, 868, and 872, the method continues at step 860 where theimproved computer compares the retrieved patent data from a correlatedMTU with the patent data of the document. The patent data includes themention of one or more patents and/or patent applications based on oneor more of patent title, patent number, patent application serialnumber, filing date, issuance date, etc.

The method continues at step 876 where the improved computer determineswhether the correlation of patent data of the document with the patentdata of the MTU is above an upper threshold. If yes, the methodcontinues at step 878 where the improved computer definitivelydetermines that the patent data of the document correlates (relates to,is similar to, is the same as, etc.) with the patent data of the MTU.

If the answer to step 876 was no, the method continues at step 880 wherethe improved computer determines whether the correlation of patent dataof the document with the patent data of the MTU is below a lowerthreshold. If yes, the method continues at step 882 where the improvedcomputer indicates that there is no patent data correlation.

If the answer to step 880 was no, the method continues at step 884 wherethe improved computer indicates that the correlation of patent data ofthe document with the patent data of the MTU is inconclusive. The methodcontinues at step 886 where the improved computer flags the patent dataof the document for subsequent analysis with respect to the MTU. Notethat, as the MTU record continues to add data, the added data may assistin a subsequent analysis of the patent data. The method continues fromsteps 878, 882, and 886 to step 676 of FIG. 126 .

FIGS. 129A through 129F are diagrams of other examples of ingesting MSBTdocuments by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technologyregarding data of an MSBT document. FIG. 129A illustrates an example ofgenerating an MSBT name section summary, which includes an MSBT documentname of AAAAA; an MSBT document data type of FINANCIAL; an MSBT documentauthor of BBBBB; an MSBT document format of REPORT; an MSBT documentsource type of BUSINESS; and a confidence factor of ZZZZZZ.

FIG. 129B illustrates an example of generating a brief description 678of the subject manner of an example MSBT document. From the name summarysection 676 and other data, the improved computer generates a summary ofthe MSBT document. For example, “This financial report providesfinancial data regarding the annual sales of products AA & AB on acountry by country basis for the years of 20xx to 20yy.”

FIG. 129C illustrates an example of generating a summary 680 of the MTUsubject matter categories of an MSBT document. For example, the sciencecategory is communications; there is no manufacturing data; theproduct/service is regarding products AA and AB; the market impact isregarding annual sales data for 20xx to 20yy in countries XYZ; there isnot functional description (i.e., no technical discussion); there is notMTU composition data of products AA and/or of AB; and there is MTUinclusion data regarding products AA and/or AB, which is/are used inproduct MM.

FIG. 129D illustrates an example of generating a summary 682 of MTU techboundaries of the MSBT document. For example, the UVP data (e.g., thewhy build) includes new user interface firmware; the marketable featuredata (e.g., the why buy) includes ease of use for customers and minimallearning curve; the technical challenge data includes emulate human tohuman touch; there is no patent data; there is not solution data; andthe patent data includes one issued US patent.

FIG. 129E illustrates an example of generating a summary 684 of the datathat didn't fit an MTU technology boundary category. For example, dataelement #1 is regarding an operational aspect of a listed product but istoo generalized to categorizes as an MTU boundary. As another example,data element #2 is regarding a solution is too non-descriptive tocategorizes as a solution. The improved computer flags, at step 684-1,data elements 1 and 2 for re-evaluation at a subsequent time.

FIG. 129F illustrates an example of generating a summary 684 of the datathat didn't fit an MTU subject matter category. For example, dataelement #3 is regarding a term that is related to science but is toogeneralized to categorizes as science category dat. As another example,data element #4 is an image regarding the product but is toonon-descriptive to categorizes it as MTU composition data. The improvedcomputer flags, at step 684-1, data elements 3 and 4 for re-evaluationat a subsequent time.

FIGS. 130A and 130B are a logic diagram of another example of ingestingMSBT documents by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technology.FIG. 130A is a repeat of the logic diagram of FIG. 123 with the steps ofMSBT document filter and create metadata.

FIG. 130B is an example of creating metadata for an MSBT document. Inthis example, the improved computer reviews the MSBT name sectionsummary, the summary of the MTU subject matter categories, the briefdescription of the subject matter, the summary of the MTU technicalboundaries, the summary of the inclusive data with respect to techboundaries, and the summary of the inconclusive data with respect to MTUsubject matter to generate the metadata. In addition, the improvedcomputer includes the filter score for the document in the metadata. Thefiltering is discussed in greater detail with reference to FIG. 131 .

For example, but not meant as an exhaustive example, the metadataincludes an indication as to whether this document is a republication ofan original document; whether this document is a new version or neweditions of an original document; the publication date; the providerinformation and/or publisher information, the length of the document, alist of documents that have cited this document, a list of documentscited by this document, and/or the filter score.

FIG. 131 is a logic diagram of another example of ingesting MSBTdocuments by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technologyregarding the filtering of MSBT documents to generate an applicabilityscore. The improved computer executes an MSBT document filter function890 to generate a filter score, which is measure of how applicable thedocument is to create a new MTU and/or updating an existing MTU.

In this example, the improved computer reviews the MSBT name sectionsummary, the summary of the MTU subject matter categories, the briefdescription of the subject matter, the summary of the MTU technicalboundaries, the summary of the inclusive data with respect to techboundaries, and the summary of the inconclusive data with respect to MTUsubject matter to generate the filter score 902. This data is ingestedinto the MSBT document filter function 890, which includes the functionsof subject matter category filter function 892, a tech boundary filterfunction 894, a subject matter inconclusive data filter function 896,and a tech boundary inconclusive data filter function 898.

The improved computer executes the subject matter category filterfunction 892 to generate a subject matter sufficiency score based on thenumber of definitive subject matter correlations. For example, if thedocument has no data regarding subject matter categories (e.g., a lowthreshold) that definitively correlated with MTU subject mattercategories, then the subject matter score is low (e.g., 1 or 2 on ascale from 1 to 10). If, however, the document has data regardingmultiple subject matter categories (e.g., a high threshold) thatdefinitively correlate with the MTU subject matter categories, then thesubject matter score is high (e.g., 7 to 9 on a scale from 1 to 10; 10if all categories have a definitive correlation).

The improved computer executes the tech category filter function 892 togenerate a tech boundary sufficiency score based on the number ofdefinitive tech boundary correlations. For example, if the document hasno data regarding tech boundary categories (e.g., a low threshold) thatdefinitively correlated with MTU tech boundary categories, then the techboundary score is low (e.g., 1 or 2 on a scale from 1 to 10). If,however, the document has data regarding multiple tech boundarycategories (e.g., a high threshold) that definitively correlate with theMTU tech boundary categories, then the tech boundary score is high(e.g., 7 to 9 on a scale from 1 to 10; 10 if all categories have adefinitive correlation).

The improved computer executes the subject matter inconclusive datafilter function 896 to generate a subject matter inconclusive data scorebased on the number of inconclusive subject matter correlations. Forexample, if the document has no inconclusive data regarding subjectmatter categories (e.g., a low threshold), then the inconclusive subjectmatter score is low (e.g., 1 or 2 on a scale from 1 to 10). If, however,the document has multiple inconclusive data regarding multiple subjectmatter categories (e.g., a high threshold), then the inconclusivesubject matter score is high (e.g., 7 to 9 on a scale from 1 to 10).

The improved computer executes the tech category inconclusive datafilter function 898 to generate a tech boundary inconclusive data scorebased on the number of inconclusive tech boundary correlations. Forexample, if the document has no inconclusive data regarding techboundary categories (e.g., a low threshold), then the tech boundaryscore is low (e.g., 1 or 2 on a scale from 1 to 10). If, however, thedocument has inconclusive data regarding multiple tech boundarycategories (e.g., a high threshold), then the tech boundary score ishigh (e.g., 7 to 9 on a scale from 1 to 10; 10 if all categories have adefinitive correlation).

The improved computer executes the aggregating filter function 900 tocombine the scores from functions 892-898 to produce the filter score902. Depending on the format type, data type, and/or data source type,the improved computer adjusts weighting factors of the scores fromfunctions 892-898. For example, the document is a datasheet, whichtypically involves technical data, the MTU boundary score will beweighted heavier than the other scores. As another example, weightingfactors for the inconclusive data scores is lower than the weightingfactors for the conclusive data scores.

FIG. 132 is a logic diagram of another example of a method of ingestingMSBT documents by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technology.The method begins at step 910 where the improved computer retrievesscanning rules for scanning an MSBT document based on the documentformat type. For example, the improved computer executes an embeddedmethod to retrieve the appropriate set of scanning rules.

The embedded method begins at step 924 where the improved computeridentities the data format of the document. The method continues at step926 where the improved computer determines whether the document formattype is a data sheet. If yes, the method continues at step 928 where theimproved computer retrieves data sheet term recognition rules. Anexample of data sheet term recognition rules is discussed with referenceto FIGS. 133 and 134.

If not, the method continues at step 930 where the improved computerwhether the document format type is marketing material. If yes, themethod continues at step 932 where the improved computer retrievesmarketing material term recognition rules.

If not, the method continues at step 934 where the improved computerwhether the document format type is a study. If yes, the methodcontinues at step 936 where the improved computer retrieves marketingmaterial term recognition rules. If not, the method continues at step938 where the improved computer determines whether the document formattype is an advertisement (e.g., sales material). If yes, the methodcontinues at step 940 where the improved computer retrievesadvertisement term recognition rules.

If not, the method continues at step 942 where the improved computerdetermines whether the document format type is an article. If yes, themethod continues at step 944 where the improved computer retrievesarticle term recognition rules. If not, the method continues at step 946where the improved computer determines whether the document format typeis a white paper. If yes, the method continues at step 948 where theimproved computer retrieves white paper term recognition rules. If not,the method continues at step 950 where the improved computer retrievesgeneral term recognition rules.

The main method continues at step 912 where the improved computer scansa document in accordance with the rules to identify an MSBT term. Asused herein, an MSBT term includes one or more words, one or moresymbols, and/or one or more characters to describe a potentiallyrelevant piece of information regarding an MTU. For example, but notmeant as an exhaustive example, an MSBT term is regarding technicalinformation, use information, financial information, exploitationinformation, expansion information, generational information, phaseinformation, innovation information, etc.

The method continues at step 914 where the improved computer compares anidentified term with existing terms (e.g., name and meaning). The methodcontinues at step 916 where the improved computer determines whether thecomparison was favorable. If yes, the method continues at step 918 wherethe improved computer determines that the term is existing and, asappropriate, updates its meaning in a term section of MSBT database. Ifnot, the method continues at step 920 where the improved computerdetermines that the term is new and creates a request for a new MSBTterm database record.

FIG. 133 is a diagram of another example of ingesting a datasheet by anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology. The data sheetis shown to include a plurality of sections: company name, productimage, product name, product schematic diagram, product description,product features, produces uses, and product specifications. When theMSBT ingest & MTU classify unit 280 of the improved computer ingests adata sheet, it identifies the data sheet's various sections. The unit280 processes the various sections as discussed with reference to FIG.134 .

FIG. 134 is a logic diagram of an example of a method of ingesting adata sheet by the MSBT ingest & MTU classify unit 280 of the improvedcomputer. The method begins at step 960 where the improved computeridentifies sections of a data sheet as illustrated in FIG. 133 . Themethod continues at step 962 where the improved computer identifiesterms per section based on the rules for a data sheet, where eachsection includes specific types of information.

The method continues at step 964 where the improved computer determineswhether an identified term is a product name. The improved computeranalyzes the term in light of the section it's from and the words,symbols, and/or characters. If the term was extracted from the productname section of a data sheet and the words, symbols, and/or charactersare consistent with product naming conventions, the improved computeridentifies the term as a product name.

If the term is a product name, the method continues at step 966 wherethe improved computer records the product name as the subject matter ofthe data sheet, which may corresponds to an existing MTU or a potentialnew MTU. The method continues at step 968 where the improved computerdetermines whether there are more terms to process. If not, the methodis done. If yes, the method repeats at step 964.

If, at step 964, the term is not a product name, the method continues atstep 970 where the improved computer determines whether the term isregarding a marketable feature. If the term was extracted from theproduct features section of a data sheet and the words, symbols, and/orcharacters are consistent with features description conventions, theimproved computer identifies the term as a marketable feature. Themethod continues at step 972 where the improved computer records theterm as a marketable feature. The method continues at step 974 where theimproved computer determines whether there are more terms to process. Ifnot, the method is done. If yes, the method repeats at step 964.

If, at step 970, the term is not a marketable feature, the methodcontinues at step 976 where the improved computer determines whether theterm is regarding use of the product. If the term was extracted from theproduct use section of a data sheet and the words, symbols, and/orcharacters are consistent with product use description conventions, theimproved computer identifies the term as a marketable feature. Themethod continues at step 978 where the improved computer records theterm as a use of the product, which corresponds to MTU inclusion data.The method continues at step 980 where the improved computer determineswhether there are more terms to process. If not, the method is done. Ifyes, the method repeats at step 964.

If, at step 976, the term is not a use of the product, the methodcontinues at step 982 where the improved computer determines whether theterm is regarding a functional aspect of the product. If the term wasextracted from the product description section of a data sheet and thewords, symbols, and/or characters are consistent with technicaldescription conventions, the improved computer identifies the term as atechnical discussion of an aspect of the product. The method continuesat step 984 where the improved computer records the term as a technicalaspect of the product, which corresponds to MTU composition data. Themethod continues at step 986 where the improved computer determineswhether there are more terms to process. If not, the method is done. Ifyes, the method repeats at step 964.

If, at step 982, the term is not regarding a functional aspect of theproduct, the method continues at step 988 where the improved computerdetermines whether there are more terms to process. If not, the methodis done. If yes, the method repeats at step 964.

FIG. 135 is a diagram of another example of document partitioning by anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology. In particular,this figure illustrates the MSBT ingest & MTU classify unit 280 usingexisting product names, existing features, existing uses, existingfunctional terms, existing technical challenge terms, and/or existingunique value propositions (UVP) to help identify one or more terms in anew MSBT document.

FIG. 136 is a logic diagram of an example of a method of ingesting adata sheet by the MSBT ingest & MTU classify unit 280 of the improvedcomputer based on the information of FIG. 135 . The method begins atstep 990 where the improved computer determines whether a documentincludes a known UVP based on the product name associated with thedocument and based on other documents that include the product name. Ifyes, the method continues at step 992 where the improved computer addsthe UVP to the record request for the MSBT document under analysis.

After step 992 or if the answer to step 990 was no, the method continuesat step 994 where the improved computer determines whether the documentincludes a known UVP based on features, uses, and/or functions in otherdocuments that include the product name and/or other documents thatincludes similar features, uses, and/or functions of the presentdocument under analysis. If yes, the method continues at step 996 wherethe improved computer adds the UVP to the record request for the MSBTdocument under analysis.

After step 996 or if the answer to step 994 was no, the method continuesat step 998 where the improved computer determines whether the documentincludes a new UVP based on features, uses, and/or functions in otherdocuments that include the product name and/or other documents thatincludes similar features, uses, and/or functions of the presentdocument under analysis.

If yes, the method continues at step 1000 where the improved computeradds the UVP to the record request for the MSBT document under analysis.The method continues at step 1002 where the improved computer adds thenew UVP to the list of known UVPs. If the answer to step 998 was no, themethod continues at step 1004 where the improved computer records theUVPs identified, if any.

FIG. 137 is a diagram of an example of MTU tagging a document by anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology. In thisfigure, one or more MTU units are retrieved by the improved computer todetermine if the is sufficient data correlation between the MTU recordand the MSBT document record to tag the MSBT document records with theMTU name. For example, the improved computer compares the various fieldsbetween the two records for correlation. An example of this is shown inFIG. 138 .

FIG. 138 is a diagram of another example of MTU tagging a document by anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology. In thisfigure, the MSBT record includes the data fields of documentdescription, product/service data, science category, market impact data,manufacturing data, UVPs, marketable features, technical challenges,problems, inventive embodiments, listed patents, and standards. The MTUrecords includes fields for marketing data, advertising data, financialdata, business data, market data, technical data, patent data,product/service data, science category, market impact data,manufacturing data, UVPs, marketable features, technical challenges,problems, inventive embodiments, listed patents, and standards.

The document description field of the MSBT record should correlate toone or more of the fields for marketing data, advertising data,financial data, business data, market data, technical data, and patentdata of the MTU record. For example, if the MSBT document is regardingfinancial data, the document description field of the MSBT record iscorrelated to the financial data field of the MTU record. If thedocument description field of the MSBT record includes insufficient datato correlate to one of the fields of the MTU record, the documentdescription field of the MSBT record is uncorrelated with the MTUrecords.

For each of the other fields of the MSBT record, the improved computerdetermines whether the field includes sufficient data with itscorresponding field in the MTU record. If yes, the improved computercorrelates the fields. If not, the field of the MSBT records isuncorrelated. The higher level of correlation between the fields of theMSBT record and MTU record, the more likely the MSBT record will betagged (e.g., MTU classified) with the name of the MTU.

FIGS. 139A through 139D are diagrams of examples regarding MTU tagging adocument by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technology.In these figures, the overlap between the MSBT data and the MTU datacorresponds to the number of fields that were correlated as discussedwith reference to FIG. 138 . As shown in FIG. 139A, there is someoverlap (e.g., about 10% to 30% of the MSBT data overlaps with the MTUdata), which creates an uncertainty if there is sufficient correlationto tag the MSBT with MTU #1. So, the MSBT record is not tagged with theMTU #1 name but is flagged for subsequent analysis.

As shown in FIG. 139B, there is very little overlap (e.g., less than 5%of the MSBT data overlaps with the MTU data), which creates certaintythat there is insufficient correlation to tag the MSBT with MTU #2.

As shown in FIGS. 139C and 139D, there is significant overlap (e.g.,more than 50% of the MSBT data overlaps with the MTU data), whichcreates certainty that there is sufficient correlation to tag the MSBTwith MTU #3 and with MTU #4.

FIG. 140 is a logic diagram of an example of a method for MTU tagging adocument by an MSBTP (marketing, sales, business, technology, andpatent) data gathering section of an improved computer for technology.The method begins at step 1010 where the improved computer determineswhether the MSBT document includes in the body of the document, the nameof an MTU. If yes, the method continues at step 1012 where the improvedcomputer tags the MSBT record for the document with the MTU.

If the answer to step 1010 was no, the method continues at step 1014where the improved computer reviews other document authored by the sameauthor. The method continues at step 1016 where the improved computerdetermines whether the document description of the present documentcorresponds to the document description of one or more other documents.If yes, the method continues at step 1018 where the improved computerdetermines whether an MTU classification of one or more of the otherdocument is an appropriate MTU classification for the present document.If yes, the method continues at step 1020 where the improved computertags the document with the one or more appropriate MTU classifications.

If the answer to step 1016 or 1018 was no, the method continues at step1022 where the improved computer reviews other document provided by thesame provider. The method continues at step 1024 where the improvedcomputer determines whether the document description of the presentdocument corresponds to the document description of one or more otherdocuments. If yes, the method continues at step 1026 where the improvedcomputer determines whether an MTU classification of one or more of theother document is an appropriate MTU classification for the presentdocument. If yes, the method continues at step 1028 where the improvedcomputer tags the document with the one or more appropriate MTUclassifications.

If the answer to step 1024 or 1026 was no, the method continues at step1030 where the improved computer reviews other document sourced by thesame data source. The method continues at step 1032 where the improvedcomputer determines whether the document description of the presentdocument corresponds to the document description of one or more otherdocuments. If yes, the method continues at step 1034 where the improvedcomputer determines whether an MTU classification of one or more of theother document is an appropriate MTU classification for the presentdocument. If yes, the method continues at step 1036 where the improvedcomputer tags the document with the one or more appropriate MTUclassifications.

If the answer to step 1032 or 1034 was no, the method continues at step1038 where the improved computer tags the MSBT document with the MTUclassification of undecided or undecided/potential new MTU.

FIG. 141 is a logic diagram of an example of a method for generating anew MSBT data record for an MSBT document by an MSBTP (marketing, sales,business, technology, and patent) data gathering section of an improvedcomputer for technology. The method begins at step 1040 where theimproved computer receives MSBT record information regarding an MSBTdocument. The method continues at step 1042 where the improved computerdetermines whether the record is an original publication. If yes, themethod continues at step 1044 where the improved computer generates anew MSBT record request. The method continues at step 1046 where theimproved computer sends the request to the MSBT database, which createsthe record.

If the answer to step 1042 was no, the method continues at step 1048where the improved computer determines whether the document is a newversion or a new edition of an original document (e.g., has differencein comparison to the original document). If yes, the method continues atstep 1058 where the improved computer determines whether to create a newMSBT database record for the new version or new edition. In anembodiment, the decision to create a new record for new versions and fornew editions.

For a new record, the method continues at step 1060 where the improvedcomputer generates a new record request for the new version or newedition document. The method continues at step 1062 where the improvedcomputer sends the request to the MSBT database, which creates therecord.

If the answer to step 1048 was no or the answer to step 1058 was update,the method continues at step 1050 where the improved computer retrievesthe MSBT record for the original document. The method continues at step1502 where the improved computer determines the changes between theoriginal document and the new version or new edition. The methodcontinues at step 1054 where the improved computer generates an updatethe MSBT record request based on the determined differences. The methodcontinues at step 1056 where the improved computer sends the request tothe MSBT database, which updates the record.

FIG. 142 is a schematic block diagram of a further embodiment of anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology ingesting andprocessing patents (issued and pending).

In this Figure, the functional operations of the patent data identify &gather MTU system application, the patent data dissection, patent termidentify, & MTU interpret MTU system application, the MTU tagging of apatent document MTU system application, annotated patent database recordcreate MTU system application and patent term database record create MTUsystem application are discussed.

The patent data identify & gather MTU system application includes foursub-programs: initial data population, on-going data population,on-going refinement, and vetting patent data. The improved computer'sexecution of this MTU system application is discussed with reference toFIG. 143 .

When the improved computer executes the patent data dissection, patentterm identify, & MTU interpret MTU system application, it follows abasic flow chart of identifying information about the patent, look forrelevant MTU orientated data, apply a patent filter function, create ageneral discussion of the patent, and create metadata for the patent.Information about the patent includes general patent information oftitle, inventor(s), assignee, IPC classification, listed prior art, theapplication type, status, country, etc.

The improved computer seeks patent terms and MTU orientated data frompatents it ingests. A patent term is a claim term or technical term. TheMTU orientated data includes, but is not limited to, science categorydata, product/service data, function data, a descriptive image, marketimpact data, a technical boundary (e.g., unique value proposition,marketable feature, technical challenge, problem, inventive concept,implementation element, implementation mechanism, implementationvariant, solution, and/or inventive embodiment), manufacturing data,and/or a technical image.

The improved computer executes the patent filter to determine, based onthe information about the patent, the patent terms, and the identifiedMTU orientated data, the usability of patent. In general, the improvedcomputer determines the usefulness of a patent for identifying new MTUsand/or for further defining existing MTUs. The filtering of a patent issimilar to the filtering of an MSBT document filtering, which wasdiscussed with reference to FIG. 131 .

The improved computer creates a discussion of the document if it hassome measure of usability. The improved computer follows a similarapproach to generating discussion of a patent as it does for generatinga discussion of an MSBT document.

The improved computer creates metadata for the patent if it has somemeasure of usability. For example, the metadata includes, but is notlimited to, source of patent, number of pages, number of figures, etc.The improved computer also creates metadata for a patent term.

The improved computer tags patents and patent terms as discussed withreference to FIGS. 144A-144G. The improved computer creates a requestfor new annotated patent database record and/or a request for updatingan existing annotated patent database record as discussed with referenceto FIG. 145 and creates a request for new patent term database recordand/or a request for updating an existing patent term database record asdiscussed with reference to FIG. 146 .

FIG. 143 is a schematic block diagram of a further embodiment of anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology regardingingesting patents and patent applications. The improved computerexecutes the initial data populate sub-program based on search criteriato identify patents of various types, of various status, and/or fromvarious countries. See FIG. 113 for examples of types, status, andcountries.

The search criteria includes, but is not limited to, patents identifiedin MSBT documents, information disclosure statements (IDS), patentoffice classification (e.g., IPC), patent claim terms, cited prior art,patent holders (e.g., inventors, applicants, assignees, etc.), patentslisted by a product provider (e.g., a manufacturer, a distributor, aproduct retailor, etc.), patent priority data to identify parent and/orsibling patents, and/or patent abstracts. For patents found via one ormore the search criteria, the improved computer vets them. The vettingof a patent is similar to the vetting of an MSBT document, which wasdiscussed with reference to FIG. 125 .

The improved computer executes the on-going data population sub-programto identify newly published patents of various types, of various status,and from various countries. To do this, the improved computer interfaceswith one or more patent services and/or with one or more patent offices.In an implementation, the improved seeks to ingest patents in batchesregarding a technology category and/or one or more technology mapsthereof. For example, the improved computer ingests medical technologypatents in one or more batches and ingests communication technologypatents in one or more other batches.

The improved computer executes the on-going data refinement sub-programto identify changes to existing patents (e.g., annotated patents in theannotated patent database). For example, the improved computer updatesan existing annotated patent database record when the application typechanges, the status changes, and/or a foreign counterpart is filed. Forexample, the application type changes include, but is not limited to, anon-provisional patent application is filed claiming priority to apending provisional application, and a US or foreign national utilitypatent application is file claiming priority to a pending PCTapplication. As another example, the status change includes, but is notlimited to, a pending patent application issues and an issued patentexpires.

The improved computer executes the on-going data refinement sub-programto identify changes to existing patents based on one or more searchcriteria. The search criteria includes, but is not limited to,assignment changes, standards submissions, standards acceptance,abandonments, re-exam requests, IPR (inter party re-exams), assertion inlitigation, and used for licensing.

The improved computer executes the initial data population sub-programonce to initially populate the annotated patent database and the patentterm database. The improved computer executes the on-going datapopulation and on-going data refinement sub-programs routinely (e.g.,continually, periodically, etc.). The improved computer vets each newlyreceived patents and/or piece of data regarding patents before adding ita database.

FIGS. 144A through 144G are a logic diagram of an example of a methodfor ingesting patents and patent applications by an MSBTP (marketing,sales, business, technology, and patent) data gathering section of animproved computer for technology. The method begins at step 1070 wherethe improved computer determines whether the figures are more than justboxes with numbers. If not, the method continues at step 1074 where theimproved computer determines whether to create new figures. If not, themethod continues at step 1078 where the improved computer identifiesdisclosed notions from the specification in accordance with patentdisclosure categories (e.g., problem set up, solution & novelty,technical description, benefit of solution, technical environment & useof invention, and patent law interpretation).

If the answer to step 1074 was yes, the method continues at step 1076where the improved computer creates new figures with descriptivecomponents that are consistent with MTU classifications and symbols. Inan example, the improved computer augments the existing figures withdescriptive terms. In another example, the improved computer generatesnew figures based on the specification and the claims. The creation ofthe new figures may further be based on the existing figures.

From step 1076 or for a yes answer from step 1070, the method continuesat step 1072 where the improved computer identifies disclosed notionsfrom the specification in accordance with patent disclosure categories.The method continues at step 1080 where the improved computer identifiesclaim terms from the independent claims and from the dependent claims.

For example, and as shown in FIG. 144B, the improved computer analysesthe specification (and figures, if descriptive) to identify tech termsand analyses the claims to identify claim terms. The tech terms andclaim terms are patent terms, which are stored in the patent termdatabase. The improved computer interprets the words, sentences,paragraphs, patent section, and/or figure description of thespecification, the identified tech terms, and/or the identified claimterms, to identify one or more disclosed notions that pertain to one ormore patent disclosure categories.

For example, a disclosed notion of “the combination of XYZ increasesefficiency” pertains to the problem set up and benefit of the solutionpatent disclosure categories. As another example, a disclosed notion of“product AA includes XYZ” pertains to the technical environment & use ofinvention patent disclosure category. As another example, a disclosednotion of “XYZ functions to perform A to modify B and then performs C onthe modified B to produce D” pertains to the solution & novelty nuggetsand the technical description of the patent disclosure categories. Notethat a quality patent application is one from which the patentdisclosure categories can be readily identified, the specification andfigures support, define, and enable the claims, and the claims haveidentifiable novelty nuggets.

The method continues at step 1082 of FIG. 144C where the improvedcomputer generates, if possible (e.g., there is at least one relevantdisclosed notion), a summary of MTU tech challenge data and/or MTUproblem data disclosed in the patent based on the disclosed notionregarding the patent disclosure category of problem set up. The methodcontinues at step 1084 where the improved computer generates, ifpossible, a summary of MTU inventive embodiment data and/or MTUmanufacturing data disclosed in the patent based on the claims andfurther based on the disclosed notions regarding the patent disclosurecategories of solution & novelty nuggets and technical description.

The method continues at step 1086 where the improved computer generates,if possible, a summary of MTU UVP data and/or MTU marketable featuresdata disclosed in the patent based on the disclosed notions regardingthe patent disclosure category of benefit of the invention. The methodcontinues at step 1088 where the improved computer generates, ifpossible, a summary of MTU product/service data, MTU science categorydata, and/or MTU standards data disclosed in the patent based on thedisclosed notions regarding the patent disclosure categories oftechnical description and technical environment & use.

FIG. 144D is an example of the steps 1082-1088 of FIG. 144C. In thisexample, the problem set up disclosed notions help identify dataregarding the MTU data categories (or technology quantifying datacategories) of technology challenges and problems. The solution &novelty nugget disclosed notions and the technical description disclosednotions help identify data regarding the MTU data categories ofinventive embodiments and manufacturing data. The benefit of theinvention disclosed notions help identify data regarding the MTU datacategories of UVPs and marketable features. The technical environment &use disclosed notions help identify data regarding the MTU datacategories of product/service, standards, and science categories.

The method continues at step 1090 of FIG. 144E where the improvedcomputer, for MTU classification of a patent, selects a technology mapand an initial technology tier of a science category based on the MTUdata summaries and the general patent information. The selection may bea default selection to a particular MTU of the map or involve initialanalysis to select the MTU. The method continues at step 1092 where theimproved computer selects an MTU of the technology category tier basedon the MTU data summaries and the general patent information.

The method continues at step 1094 where the improved computer calculatesa correlation score based on the correlation of the data of MTU datasummaries and the data of the selected MTU. The method continues at step196 where the improved computer determines whether the score is above anupper threshold (e.g., a high correlation score, which indicates thatthe patent is definitively regarding the selected MTU). If yes, themethod continues at step 1098 where the improved computer flags thepatent for MTU classification with the selected MTU.

The method continues at step 1100 where the improved computer determineswhether this is another MTU of the current tier that has been selected,a, MTU from a different tier that has been selected, of the MTU datasummaries suggest more than one MTU. If not, the method continues atstep 1102 where the improved computer executes the MTU tagging of apatent system application to tag the patent with the selected MTU. Ifthere is another selected MTU of the same tier, the method repeats atstep 1090. If there is a selected MTU of another tier, the methodrepeats at step 1092.

If the answer at step 1096 was no, the method continues at step 1104where the improved computer determines whether score is below a lowerthreshold (e.g., a low correlation score, which indicates that thepatent is definitively not regarding the selected MTU). If yes, themethod continues at step 1100.

If the answer at step 1104 was no, the method continues at step 1106where the improved computer accesses the patent term database to findpatents that include like patent terms as the present patent. The methodcontinues at step 1108 where the improved computer accesses theannotated patent database to find like patents based on the generaldescription of the present patent. The method continues at step 1110where the improved computer reviews the like patents to determine ifthey provide insight into the MTU data summaries of the present patentapplication.

If not, the method continues at step 1114 where the improved computerflags the patent for an MTU classification of undecided orundecided/potential new MTU. The method then continues at step 1100. Ifthe answer to step 1110 is yes, the method continues at step 1112 wherethe improved computer updates one or more of the MTU data summaries ofthe patent. The method then continues at step 1094.

FIG. 144F is an example of selecting a technology map and an MTU forclassifying a patent. In this example, the improved computer selects theMTU map regarding cell phone of portable computing devices of computingdevices of CIE (communications, information, and electrical) technologybased on an initial review of the general patent information and the MTUdata summaries. The improved computer then selects the touchscreen MTUto start the method of FIG. 144E.

FIG. 144G is an example of the data used by the improved computer toreview a patent (of any type, of any status, from any country). The dataincludes one or more patent term records, one or more annotated patentrecords, and/or one or more MTU records. Each records includes a namesection and its own MTU orientated data section. The review includes aninitial MTU classification, updating an MTU classification, updating MTUdata summaries, and/or updating other sections of the correspondingannotated patent record.

FIG. 145 is a logic diagram of an example of a method for generating anew annotated patent record for an MSBT document by an MSBTP (marketing,sales, business, technology, and patent) data gathering section of animproved computer for technology. The method begins at step 1120 wherethe improved computer reviews patent information. The method continuesat step 1122 where the improved computer determines whether an annotatedpatent records exists for the patent based on the patent information(e.g., patent number, country, filing date, patent application serialnumber, etc.).

If yes, the method continues at step 1128 where the improved computergenerates an update annotated patent database record request regardingnew patent information. The method continues at step 1130 where theimproved computer sends the request and the new patent information tothe annotated patent database, which updates the existing annotatedpatent record with the new data.

If the answer to step 1122 was no, the method continues at step 1124where the improved computer generates a new annotated patent databaserecord request regarding the patent. The method continues at step 1126where the improved computer sends the request and the patent informationto the annotated patent database, which creates a new annotated patentrecord for the patent.

FIG. 146 is a logic diagram of an example of a method for generating anew patent term record for an MSBT document by an MSBTP (marketing,sales, business, technology, and patent) data gathering section of animproved computer for technology. The method begins at step 1140 wherethe improved computer reviews patent term information. The methodcontinues at step 1142 where the improved computer determines whether apatent term records exists for the patent term based on the patent terminformation (e.g., patent term name, patent term synonym, discussion ofpatent term, etc.).

If yes, the method continues at step 1148 where the improved computergenerates an update patent term database record request regarding newpatent term information. The method continues at step 1150 where theimproved computer sends the request and the new patent term informationto the patent term database, which updates the existing patent termrecord with the new data.

If the answer to step 1142 was no, the method continues at step 1144where the improved computer generates a new patent term database recordrequest regarding the patent term. The method continues at step 1166where the improved computer sends the request and the patent terminformation to the patent term database, which creates a new patent termrecord for the patent term.

FIG. 147 is a logic diagram of an example of a method for identifying anew market-tech unit (MTU) by an MSBTP (marketing, sales, business,technology, and patent) data gathering section of an improved computerfor technology. The method begins at steps 1160, 1162, and 1164. At step1160, the improved computer retrieves MSBT records having an MTUclassification of undecided/potential new MTU for a specific potentialnew MTU. At step 1162, the improved computer retrieves annotated patentrecords having an MTU classification of undecided/potential new MTU forthe specific potential new MTU. At step 1164, the improved computerretrieves patent term records having an MTU classification ofundecided/potential new MTU for the specific potential new MTU.

From steps 1160, 1162, and 1164, the method continues at steps 1166,1168, and 1170. At step 1166, the improved computer identifies updatesto the retrieved MSBT records since the last running of this method forthis specific potential new MTU. At step 1168, the improved computeridentifies updates to the retrieved annotated patent records since thelast running of this method for this specific potential new MTU. At step1170, the improved computer identifies updates to the retrieved patentterm records since the last running of this method for this specificpotential new MTU.

From steps 1166, 1168, and 1170, the method continues at step 1172 wherethe improved computer compiles the updates from the various recordsbased on MTU orientated data categories. The method continues at step1174 where the improved computer adds the compiled updates to existingMTU data summaries regarding the potential new MTU to createmost-recent-updated MTU data summaries.

The method continues at step 1176 where the improved computer determineswhether analysis of the most-recent-updated MTU data summaries exceedsan upper threshold for establishing a new MTU. The upper thresholdcorresponds to sufficient data to establish the new MTU, which includes,at a minimum, one or more new and definitive UVPs, one or more new anddefinitive technology challenges, and market impact data to support anew MTU. If yes, the method continues at step 1178 where the improvedcomputer initiates the creation of the new MTU and a new MTU databaserecord.

If the answer to step 1176 is no, the method continues at step 1180where the improved computer determines whether analysis of themost-recent-updated MTU data summaries is below a lower threshold forestablishing a new MTU. The lower threshold corresponds to very littleto no data to support the creation of a new MTU. If no, the methodcontinues at step 1184 where the improved computer keeps the specifiedpotential new MTU as a potential new MTU.

If yes, the method continues at step 1182 where the improved computerremoves the specified potential new MTU as a potentially new MTU andupdates the MSBT records, the annotated patent records, and the patentterm records MTU classification by removing the undecided/potential newMTU for the specified potential new MTU from the records.

As used herein, an MTU should include a manageable number of UVPs and oftechnical challenges (e.g., 1-10). The number of technical challengesdepends on the number of problems and corresponding inventions likely toevolve for each technical challenge. As a general example, it would bedesirable to keep the number inventions that have patent protectionbetween 20 and 200 per MTU. Too few inventions indicates too fine ofpartitioning of MTUs and too many inventions includes too coarse ofpartitioning of MTUs and/or generations thereof.

To track the evolution of MTUs and to assist in determining when an MTUshould be split into two or more MTUs, MSBT records, annotated patentrecords, and patent term records may include a specific MTUclassification for the current MTU and undecided/potential new MTUclassification regarding the splitting of the current MTU.

As is also used herein, a new MTU may be proprietary to a particularcustomer and is only included the private database associated with theparticular customer (i.e., it is not stored in the MTU database foraccess by the MTU user applications). As information regarding the MTUbecomes publicly available, the improved computer executes the method ofFIG. 147 and, once there is sufficiently publicly available data tosubstantiate creating a new MTU, the MTU will be added to the MTUdatabase and will no longer be deemed proprietary of the particularcustomer.

FIG. 148 is a logic diagram of an example of a method forgenerating/updating a market-tech unit (MTU) composition diagram by anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology. The methodbegins at step 1190 where the improved computer determines whether anMTU composition drawing exists. If no, the method continues at step 1192where the improved computer establishes (e.g., look up, create, modifyanother, etc.) a symbol for the MTU. Examples of establishing a symbolfor an MTU are discussed with reference to FIGS. 150A-150C.

The method continues at step 1194 where the improved computer identifiestier −1 MTUs from a technology map, from the MTU database record, etc.and may further identify tier −2 MTUs and lower tiers. The methodcontinues at step 1196 where the improved computer establishes symbolsfor the tier −1 MTUs (and lower tiers if appropriate). The methodcontinues at step 1198 where the improved computer obtains drawing rulesof the particular science category. For example, there are rules fordrawing electrical diagrams, for drawing flow charts, etc.

The method continues at step 1200 where the improved computer interpretsthe MTU data and the MTU symbols in light of the drawing rule to ensurethat the symbols comply with the rules and that there is sufficient datafor the rules to process. The method continues at step 1202 where theimproved computer applies the drawing rules on the interpreted data andsymbols to generate an MTU composition diagram.

If the answer to step 1190 was yes, the method continues at step 1204where the improved computer generates a new MTU composition diagram persteps 1192 through 1202. The method continues at step 1206 where theimproved computer compares the new diagram to the existing one. Themethod continues at step 1208 where the improved computer determines ifthere are any differences. If not, the method continues at step 1210where the improved computer does not update the existing drawing.

If yes, the method continues at step 1212 where the improved computerdetermines whether the differences are de minimis (e.g., de minimischanges are slight word differences a term but change operation of theMTU; non de minimis changes affect the operation of the MTU, whichincludes new and/or improved features, new and/or improved functions,etc.). If the changes are de minimis, the method continues at step 1214where the improved computer annotates the existing diagram with notesregarding the de minimis differences.

If the changes are not de minimis, the method continues at step 1216where the improved computer generates an updated diagram to include thenon-de minimis changes and annotates the updates. The method continuesat step 1218 where the improved computer archives the existing diagram.

The improved computer routinely executes the method of FIG. 148 tocreating and/or update MTU composition diagrams. The purpose of an MTUcomposition diagram is to provide a figure that is enablement driven, iseasy to understand, has easily recognizable elements (e.g., MTUsymbols), has clear data/signal flow (if applicable), has clearconnectivity between elements (if applicable), omits obvious features(e.g., power connections unless power is part of tech challenge), and/orhas focus on functionality with minimal theoretical discussion (limitedto no use of equations, depict what the equations do).

FIG. 149 is a logic diagram of an example of a method forgenerating/updating a market-tech unit (MTU) composition diagram by anMSBTP (marketing, sales, business, technology, and patent) datagathering section of an improved computer for technology. The methodbegins at step 1200 where the improved computer determines whether anMTU inclusion drawing exists. If no, the method continues at step 1222where the improved computer establishes (e.g., look up, create, modifyanother, etc.) a symbol for the MTU. Examples of establishing a symbolfor an MTU are discussed with reference to FIGS. 150A-150C.

The method continues at step 1224 where the improved computer identifiestier +1 MTUs from a technology map, from the MTU database record, etc.and may further identify tier +2 MTUs and higher tiers. The methodcontinues at step 1226 where the improved computer establishes symbolsfor the tier +1 MTUs (and higher tiers if appropriate). The methodcontinues at step 1228 where the improved computer obtains drawing rulesof the particular science category. For example, there are rules fordrawing electrical diagrams, for drawing flow charts, etc.

The method continues at step 1230 where the improved computer interpretsthe MTU data and the MTU symbols in light of the drawing rule to ensurethat the symbols comply with the rules and that there is sufficient datafor the rules to process. The method continues at step 1232 where theimproved computer applies the drawing rules on the interpreted data andsymbols to generate an MTU inclusion diagram.

If the answer to step 1220 was yes, the method continues at step 1234where the improved computer generates a new MTU inclusion diagram persteps 1222 through 1232. The method continues at step 1236 where theimproved computer compares the new diagram to the existing one. Themethod continues at step 1228 where the improved computer determines ifthere are any differences. If not, the method continues at step 1240where the improved computer does not update the existing drawing.

If yes, the method continues at step 1242 where the improved computerdetermines whether the differences are de minimis (e.g., de minimischanges are slight word differences a term but change operation of theMTU; non de minimis changes affect the operation of the MTU, whichincludes new and/or improved features, new and/or improved functions,etc.). If the changes are de minimis, the method continues at step 1244where the improved computer annotates the existing diagram with notesregarding the de minimis differences.

If the changes are not de minimis, the method continues at step 1246where the improved computer generates an updated diagram to include thenon-de minimis changes and annotates the updates. The method continuesat step 1248 where the improved computer archives the existing diagram.

The improved computer routinely executes the method of FIG. 149 tocreating and/or update MTU inclusion diagrams. The purpose of an MTUinclusion diagram is to provide a figure that is enablement driven, iseasy to understand, has easily recognizable elements (e.g., MTUsymbols), has clear data/signal flow (if applicable), has clearconnectivity between elements (if applicable), omits obvious features(e.g., power connections unless power is part of tech challenge), and/orhas focus on functionality with minimal theoretical discussion (limitedto no use of equations, depict what the equations do).

FIGS. 150A through 150C are a logic diagram of an example of a methodfor generating/updating a market-tech unit (MTU) symbol by an MSBTP(marketing, sales, business, technology, and patent) data gatheringsection of an improved computer for technology. The method, regardingstep 1192 of FIG. 148 and step 1222 of FIG. 149 , begins at step 1250 ofFIG. 150A where the improved computer searches a set of symbols for aparticular technology category in which the MTU lies. For example, thereare symbols for various electronic devices and/or electronic circuits.

The method continues at step 1252 where the improved computer determineswhether a symbol for the MTU exists. If yes, the method continues atstep 1254 where the improved computer uses the symbol. If a symbol doesnot exist, the method continues at step 1256 where the improved computerdetermines to modify an existing symbol. If yes, the method continues atstep 1258 where the improved computer modifies an existing symbol.

FIG. 150B illustrates an example of modifying an existing system of atelephone and a tablet. The symbol for a phone began with a graphicalrepresentation of a rotary phone. The symbol for a cell phone evolvedfrom the rotary phone to a button phone with an external antenna to atouchscreen phone with an internal antenna. The symbol for a laptopcomputer is a graphical representation of a laptop. The symbol for atablet evolved from the symbol of a laptop and a touchscreen cell phone.

Returning to the method of FIG. 150A, the method continues at step 1260where the improved computer creates a new symbol. FIG. 150C illustratesa method for creating a new symbol. The method begins at step 1262 wherethe improved computer determines whether the MTU has a physical feature(e.g., a package, a housing, a geometric shape, etc.). If yes, themethod continues at step 1264 where the improved computer generates asymbol for the MTU as a graphical representation that encompasses thephysical feature. If no, the method continues at step 1266 where theimproved computer selects a generic shape and labels it with the MTUname.

FIG. 151 is a schematic block diagram of a further embodiment of animproved computer for technology regarding use of MTU data records. Theimproved computer 70 is shown to include the user interface application78, the computing entity hardware (HW) 102, the computing entityoperating system (OS) 104, the MTU operating system (OS) 106, the MTUdatabase 264, the MSBT database 262, the patent terms database 266, theannotated patent database 268, the patent use database 270, the patentprocurement database 272, the market impact database 274, the MTU systemapplications 470, and the MTU user applications 1272.

The MTU OS 106 controls and manages the MTU system applications 470access to the system databases 262-274 and controls and manages the MTUsystem applications 470 access to the computing entity OS 104. The MTUOS 106 also controls and manages the MTU user applications 1272 accessto the system databases 262-274 and controls and manages the MTU userapplications 1272 access to the computing entity OS 104. The MTU OS 106further controls and manages the user interface application 78 access tothe MTU user applications.

The computing entity OS 104 controls and manages the MTU systemapplications 470 (via the MTU OS 106) access to the computing entityhardware 102, controls and manages the MTU user applications 1272 (viathe MTU OS 106) access to the computing entity hardware 102, andcontrols and manages the user interface application 78 (via the MTU OS106) access the computing entity hardware 102.

User computing devices 1275 send MTU queries 1270 to the improvedcomputer via the user interface application 78. For an authorized MTUquery from an authorized and authenticated user computing device, theimproved computer while executing the user interface application 78selects one or more MTU user applications 1272 to process the MTU query.The improved computer executes the one or more MTU user applications1272 via the computing entity hardware 102 under the control andmanagement of the MTU OS 106 and the computing entity OS 104 to producean MTU response 1274. The improved computer outputs the MTU response1274 to the user computing device.

FIG. 152 is a schematic block diagram of a further embodiment of animproved computer for technology that is in communication with a usercomputing device 1275. The improved computer includes, in part, thesystem databases 262-274, co-processor 111 for executing MTU OSfunctions & computing entity OS functions, co-processor 115 forexecuting user applications, the user interface unit 78, and thesubscription pricing unit 80. The MTU user applications include MTUgeneration and phase report, MTU existing patent data report, MTUexisting market impact report, MTU existing patent protection report,MTU previous and current value report, MTU future patent data report,MTU future market impact report, MTU future patent protection report,MTU future value report, MTU technology expansion report, MTU marketopportunity report, MTU expansion report, MTU patent protection expense& growth report, MTU architectural patent protection plan, MTU inventionidentification & claim drafting, MTU patent application drafting, MTUpatent prosecution drafting, MTU patent quality reports, MTU patentprotection plan execution tracking report, MTU constructive noticereport, MTU patent sale opportunity report, MTU patent purchaseopportunity report, MTU patent licensing opportunity report, MTU patentstandards report, and MTU patent spin-off or joint venture (JV)opportunity report.

Examples of the improved computer executing one or more of the MTU userapplications are discussed with reference to other figures herein. As anexample, the improved computer executes the method of FIG. 153 whichbegins at step 1280 where the improved computer, via its 10 interfacehardware receives an MTU query from a user computing device. The methodcontinues at step 1282 where the improved computer, via a co-processor,executes the MTU security OS function to quarantine and scrub the queryto ensure that the request does not include “bad actor” coding and thatis from an authenticated user computing device (e.g., is the true usercomputing device and not a spoof).

The method continues at step 1284 where the improved computer determineswhether the MTU query has been clear and should be released for furtheranalysis. If no, the method continues at step 1286 where the improvedcomputer deletes the query from quarantine, blacklists the user (e.g.,bans the user from accessing the improved computer), and/or blackliststhe user computing device (e.g., bans the user computing device fromaccessing the improved computer).

If the answer to step 1284 was yes, the method continues at step 1288where the improved computer, via co-processor, executes the MTU userinterface MTU OS function to valid the user, the user computing device,and the MTU query. For example, the improved computer verifies that theuser has a valid account, verifies that the user computing device isregistered to the user, and verifies that the user is authorized to makesuch an MTU query (e.g., the query is within the subscription of theuser).

The method continues at step 1290 where the improved computer determineswhether the user, the user computing device, and the MTU query have beenvalidated. If not, the method continues at step 1292 where the improvedcomputer sends a message to the user computing device indicating thequery was not validated. If the cause for the query not being valid wasan insufficient subscription, the improved computer includes the messagethe cost for obtaining a sufficient subscription to fulfill the query.

If the answer to step 1290 was yes, the method continues at step 1296where the improved computer, via a co-processor, executes the MTUprocess management OS function to identified MTU user applications thatare required to fulfill the MTU query. The method continues at step 1298where the improved computer, via a co-processor, executes the MTUprocess management OS function to control and manage the processes ofthe identified MTU user applications.

The method continues at step 1300 where the improved computer, via aco-processor, executes the MTU system database management OS function toretrieve data as needed for the execution of the MTU user applicationsand to store data being generated by the MTU user applications. Themethod continues at step 1302 where the improved computer determineswhether the execution of the MTU user applications is finished (i.e.,have produced an MTU response). If not, the method repeats at step 1298.If yes, the method continues at step 1304 where the improved computer,via a co-processor, executes the MTU user interface OS function tooutput the MTU response to the user computing device.

FIG. 154 is a schematic block diagram of a further embodiment of animproved computer for technology regarding generating of an existingpatent landscape report for an MTU. In this figure, the improvedcomputer receives an MTU query 1270 to generate a report for an existingpatent landscape regarding a specified MTU, or MTUs. To prepare thereport, the improved computer engages the tech-patent maturity unit 340and the existing patent landscape unit 342.

The tech patent maturity unit 340 executes the MTU user application forproducing a report regarding generation data and phase data for theMTUs. While executing this MTU user application, the tech patentmaturity unit 340 generates S-curve data for each generation detectedfor the MTU. The unit 340 determines the start date of the currentgeneration of the MTU, the time duration of the current generation andfor each of its phase, and the time that has passed since the startdate. From this information, the unit determines the current phase, thetime remaining the current phase, and the time remaining before end oflife.

The unit 340 calculates a level of innovation for the life of the MTU.To do this, the unit calculates the total number of inventions likely tobe created over the life of the current generation of the MTU. The unit340 also calculates a total number of invention types to created basedon the total number of inventions and MSBTP (marketing, sales, business,technical, and patents) data. From this data, the unit 340 determinesthe total number of inventions that should have been created to date andthe corresponding numbers for invention types. Examples of this arediscussion in preceding and/or subsequent figures.

The existing patent landscape unit 342 identifies MTU related patentsthat have issued to date and MTU related patent applications have beenfiled to date and are publicly available. In this instance, relatedmeans patents and patent applications have an MTU classification of theMTU. For the MTU related issued patents and patent applications, theunit 342 retrieves general patent data (e.g., patent holder information,filing date, title, general description, etc.)

The unit 342 generates the existing patent landscape report for the MTUbased on the retrieved patent data, the S-curve data, the phase of theS-curve data, the level of innovation data, and the level of innovationto date data. To do this, the unit 342 maps invention quantities pertime of the existing patents and patent applications to the S-curve.

The unit 342 generates the existing patent landscape report as an MTUresponse 1274 to the MTU query. The landscape reports includes the abovedata organized in the aggregate, by patent holder, by invention type, byyear, by phase, etc. From the existing patent landscape report, the dataof a particular patent holder can be extracted to produce a competitorexisting patent analysis report.

FIG. 155 is a schematic block diagram of a further embodiment of animproved computer for technology regarding generating of an existingmarket impact report for an MTU. In this figure, the improved computerreceives an MTU query 1270 to generate a report for existing marketimpact regarding a specified MTU, or MTUs. To prepare the report, theimproved computer engages the tech-patent maturity unit 340 and theexisting market impact unit 348. The tech-patent maturity unit 340operates as discussed in the preceding figure.

The market impact unit 348 retrieves existing market data regarding theMTU, existing business data regarding the MTU, and exiting financialdata regarding the MTU. From this data and the data from unit 340, theunit 348 generates the existing market impact report as an MTU response1274. Examples of this are discussed in preceding and/or subsequentfigures.

FIG. 156 is a schematic block diagram of a further embodiment of animproved computer for technology regarding generating of a reportregarding how well an MTU is protected by existing patents and existinginventions. In this figure, the improved computer receives an MTU query1270 to generate a report for how well existing inventions are patentprotected for a specified MTU, or MTUs. To prepare the report, theimproved computer engages the tech-patent maturity unit 340 and theexisting how well patent protected unit 346. The tech-patent maturityunit 340 operates as discussed in the preceding figure.

The unit 346 identifies issued and pending patent applications regardingthe MTU have been filed and/or issued to date. The unit 346 retrievespatent data for the identified existing patents and applications. Theunit 346 compares the number of existing inventions that have beenpatent protection to the number inventions that could have been patentprotected to date to determine a level of patent protection proficiencyto date. The level of patent protection proficiency is basically ameasure of how many of the total number of inventions that could havebeen patent protected to date have actually been patent protected.

The unit 346 also performs a patent quality analysis of the existingpatents and patent applications. The quality of an issued patent orpending patent application is based on the ability to clearly identifythe patent disclosure categories of problem set up, solution & noveltynuggets, technical description, benefit of solution, technicalenvironment, use of the invention, and patent law interpretation.

From the above data, the unit 346 determines how well the MTU has beenpatent protected to date. Examples of this are discussed in precedingand/or subsequent figures.

FIG. 157 is a schematic block diagram of a further embodiment of animproved computer for technology regarding generating of a reportregarding value of an MTU based on existing patents and inventionsreports. In this figure, the improved computer receives an MTU query1270 to generate a report regarding the existing value of a specifiedMTU, or MTUs. To prepare the report, the improved computer engages thetech/value patents unit 350.

The unit 350 calculates the value of an MTU based on the market impactof the MTU, how well the MTU is patent protected, and a market-patent“k” factor. The market impact data and the how well patent protecteddata are pulled from the previous report.

The unit 350 the “k” factor is a measure of how heavily marketdifferentiators depend on technology. The more important technology isto differentiate products in the marketplace, the higher the “k” factor.To calculate the “k” factor, the unit 350 retrieves market data,business data, and financial data regarding the MTU. The unit 350 alsoretrieves patent data regarding the MTU.

From the above data, the unit 350 determines the existing value of theMTU. Examples of this are discussed in preceding and/or subsequentfigures.

FIG. 158 is a schematic block diagram of a further embodiment of animproved computer for technology regarding generating of a forecastedfuture patent landscape report for an MTU. In this figure, the improvedcomputer receives an MTU query 1270 to generate a report for a futureforecasted patent landscape regarding a specified MTU, or MTUs. Toprepare the report, the improved computer engages the tech-patentmaturity unit 340 and the forecast patent landscape unit 352.

The tech patent maturity unit 340 executes the MTU user application forproducing a report regarding generation data and phase data for theMTUs. While executing this MTU user application, the tech patentmaturity unit 340 generates S-curve data for each generation detectedfor the MTU. The unit 340 determines the start date of the currentgeneration of the MTU, the time duration of the current generation andfor each of its phase, and the time that is remaining until the end oflife. From this information, the unit determines the current phase, thetime remaining the current phase, and the time remaining before end oflife.

The unit 340 calculates a level of innovation for the life of the MTU.To do this, the unit calculates the total number of inventions likely tobe created over the life of the current generation of the MTU. The unit340 also calculates a total number of invention types to created basedon the total number of inventions and MSBTP (marketing, sales, business,technical, and patents) data. From this data, the unit 340 determinesthe total number of inventions that should be created from now to theend of life and the corresponding numbers for invention types. Examplesof this are discussion in preceding and/or subsequent figures.

The forecast patent landscape unit 352 identifies MTU related patentsthat have issued to date and MTU related patent applications have beenfiled to date and are publicly available. In this instance, relatedmeans patents and patent applications have an MTU classification of theMTU. For the MTU related issued patents and patent applications, theunit 352 retrieves general patent data (e.g., patent holder information,filing date, title, general description, etc.)

From the data from unit 340, the unit 352 calculates the number ofinventions that should be invented from the present data to the end oflife of the MTU. The unit 352 also calculates the future ideal patentposition.

From the retrieved patent data and the above calculated data, the unit352 generates the forecasted future patent landscape report as an MTUresponse 1274. The landscape reports includes the above data organizedin the aggregate, by patent holder, by invention type, by year, byphase, etc. From the forecasted future patent landscape report, the dataof a particular patent holder can be extracted to produce a competitorexisting patent analysis report.

FIG. 159 is a schematic block diagram of a further embodiment of animproved computer for technology regarding generating of a forecastedfuture market impact report for an MTU. In this figure, the improvedcomputer receives an MTU query 1270 to generate a report for futuremarket impact regarding a specified MTU, or MTUs. To prepare the report,the improved computer engages the tech-patent maturity unit 340 and thefuture market impact unit 358. The tech-patent maturity unit 340operates as discussed in the preceding figure.

The market impact unit 358 retrieves future market data regarding theMTU, future business data regarding the MTU, and future financial dataregarding the MTU. From this data and the data from unit 340, the unit358 generates the future market impact report as an MTU response 1274.Examples of this are discussed in preceding and/or subsequent figures.

FIG. 160 is a schematic block diagram of a further embodiment of animproved computer for technology regarding generating of a reportregarding how well an MTU is protected by forecasted future patents andexisting inventions. In this figure, the improved computer receives anMTU query 1270 to generate a report for how well future inventions arelikely to be patent protected for a specified MTU, or MTUs. To preparethe report, the improved computer engages the tech-patent maturity unit340 and the future how well patent protected unit 356. The tech-patentmaturity unit 340 operates as discussed in the preceding figure.

The unit 356 identifies issued and pending patent applications regardingthe MTU have been filed and/or issued to date. The unit 356 retrievespatent data for the identified existing patents and applications. Theunit 356 compares the number of future inventions that are likely to bepatent protection to the total number inventions that are likely to becreated in the future to determine a level of future patent protectionproficiency.

The unit 356 also performs a patent quality estimate of future patentsand patent applications. From this data and the above data, the unit 356determines how well the MTU has been patent protected to date. Examplesof this are discussed in preceding and/or subsequent figures.

FIG. 161 is a schematic block diagram of a further embodiment of animproved computer for technology regarding generating of a reportregarding value of an MTU based on existing patents and inventionsreports. In this figure, the improved computer receives an MTU query1270 to generate a report regarding the future value of a specified MTU,or MTUs. To prepare the report, the improved computer engages thetech/value forecast patents unit 360.

The unit 360 calculates the future value of an MTU based on the futuremarket impact of the MTU, the future how well the MTU is patentprotected, and the market-patent “k” factor. The future market impactdata and the future how well patent protected data are pulled from theprevious report. The “k” factor is calculated as previously discussed.From this data, the unit 360 determines the existing value of the MTU.Examples of this are discussed in preceding and/or subsequent figures.

FIG. 162 is a schematic block diagram of an example of interactionbetween a patent plan and a budget as processed by an improved computerfor technology. In a conventional patent process, the patent preparationand prosecution budget is governed by an annual, budget-based, patentplan. Such a patent plan partitions the annual budget into domestic(e.g., U.S.) expenses and international expenses. The expenses includepatent application preparation expenses, patent prosecution expenses,patent issuance expenses, patent annuity expenses for internationalpatents, and maintenance expenses for U.S. patents. The number of newU.S. patent applications is a function of the patent budget allocatedfor U.S. patent application preparation expenses divided by the averageper U.S. patent application preparation cost.

The number of new international patent applications is a function of thepatent budget allocated for international patent application preparationexpenses divided by the average per international patent applicationpreparation cost, which is further divided by the number of countriesthe patent application will be filed in.

With an annual target patent filing number that is established based onan annual budget, a patent committee renders its decisions to fill thenumbers quota based on individual merits of the invention and aresulting patent (i.e., can it be used as a bullet for litigation). Thedecision is not based on the market impact of the technology, a desiredpatent position for the technology, and/or how a patented inventionsupports the market impact and/or desired patent position. This leads toan unfocused patent portfolio that omits too many valuable inventions.

In contrast, the re-engineered patent process executed by the newcomputer for technology (as described in more detail with reference toone or more of the previous Figures) develops a patent business plan(i.e., patent plan) based on Market-Tech Units (MTUs) in order tomaximize the value of patented technology. While the budget shownincludes the same format (e.g., partitioning the annual budget into U.S.expenses and international expenses) as conventional processing, the waythe budget is determined with respect to the re-engineered patentprocess is substantially different.

In the re-engineered patent process, the patent plan includes a patentbudget (e.g., a total spend for patents for a time period), technologyboundaries (e.g., technology classes and sub-classes), and balanceobjectives. The patent plan identifies targeted inventions and filingdecisions for a patent portfolio based on patent data, forecasting, dataanalysis, and user input as discussed in more detail with reference toat least FIG. 22 . The user inputs are adjustable and include afinancial input 306 and a patent position input 308. The financial input306 is a desired financial commitment for developing the patentportfolio over a period of time (e.g., a quarter, a year, two years,seven years, etc.) and the patent position input 308 is a desired patentposition with respect to others.

The financial input 306 is adjusted based on the market impact of one ormore market-technology areas of the portfolio and the patent ROI. Forexample, a market-technology area that has a large market impact mayrequire a larger financial commitment to adequately protect technologyand secure a desired patent ROI.

The patent position input 308 ranges from weak to superior on a slidingscale (e.g., a numerical scale where 1 corresponds to weak and 10corresponds to superior). A superior patent position corresponds to avery high probability of a favorable outcoming in a patent disputeinvolving the quantified technology. A weak patent position correspondsto a very high probability of an unfavorable outcoming in a patentdispute involving the quantified technology. A superior patent positionincludes actual inventions patent protected in the range of 35% to 80%of the ideal number of inventions. With a superior patent portfolio, thepatent holder would be able to grow and protect its market share, wouldbe able to control who participates in the market and would be able todetermine what's the cost of entry into the market. A superior patentprotection thus correlates to having a better patent position withrespect to all others in the market.

A superior patent position is not just a sheer numbers game. A superiorpatent position is achieved by creating a patent portfolio that isbalanced, has broad technology boundaries, and has no weaknesses. Assuch, a medium patent position is less balanced, has less broadtechnology boundaries, and has more weaknesses than a superior patentposition and a weak patent position is not balanced, has narrowtechnology boundaries, and has many weaknesses.

In this example, a patent preparation and prosecution budget is shown.Patent use (e.g., licensing and litigating) may be a separate budget ora separate component of the overall patent budget. From the financialinput (e.g., desired spend) and the desired patent position per MTU, thepatent plan estimates where and how money will be allocated within apatent preparation and prosecution budget. The patent preparation andprosecution budget includes a domestic budget (e.g., U.S. budget) and aninternational budget. The U.S. budget includes a budget for newapplications, prosecution, issuance, maintenance, and subsequentfilings. New applications include provisional applications andnon-provisional applications (e.g., utility, design, and plantapplications). New applications may include legal placeholder inventions(LPIs) that are filed at an additional cost to the base application fee(e.g., a bundle application). The budget for new applications includesestimated legal service fees (e.g., preparing and filing theapplication) and government filing fees. Prosecution includes officeaction responses, notice of appeals, appeal briefs, requests forcontinued examination (RCE), examiner interviews, and othercommunication with the Patent Office during the prosecution of a patent.The budget for prosecution includes the includes estimated legal servicefees (e.g., preparing and filing responses) and government filing fees.

The issuance budget includes estimated government issue fees andassociated legal service fees for issuing patents. The maintenancebudget includes estimated maintenance fees and associated legal servicefees to keep patents in force (e.g., paid at around 3, 7, and 11 yearsafter the issue date of a patent). Maintenance fees are not required fordesign or plant patents. Subsequent filings include continuationapplications, continuation-in-part applications, and divisionalapplications. A special type of continuation application to claim out anLPI is a LPI conversion application (also referred to herein as a legalplaceholder conversion (LPC) application) and may be at a differentbilling rate than a traditional continuation. The budget for subsequentfilings includes estimated legal service fees (e.g., preparing andfiling the subsequent application) and government filing fees. From theamount of new applications filed and to be filed, the new computer fortechnology is operable to estimate costs and quantities of prosecution,issuance, maintenance, and subsequent filings.

The international budget includes a budget for Patent Cooperation Treaty(PCT) applications and budgets for each selected country (e.g., CountryΣ through Country Ω) where applications are filed at the national stage(via the PCT route or directly). A PCT application makes it possible toseek patent protection for an invention simultaneously in a large numberof countries by filing a single “international” patent applicationinstead of filing several separate national or regional applications.The budget for each country includes a budget for new applications,prosecution, issuance, annuities, and subsequent filings. The budget foreach new application, prosecution, issuance, annuities, and subsequentfilings is similar to that of the U.S. budget, except that forinternational filings, annuities (similar to maintenance fees) areyearly fees paid to a foreign patent office to maintain a granted patentor patent application in force. At the time of the filing of thisapplication, official fees for annuities (also referred to as renewalfees) can range from $200-$2000 per country per year. The longer apatent holder wanted to keep their patent in force, the higher theofficial fee is per year.

Therefore, the patent plan and the budget are adjustable based off ofpatent portfolio growth goals and financial constraints. By adjustingthe budget, the patent plan may be adjusted (e.g., the patent positionmay be reduced to accommodate a lower budget). Likewise, by adjustingthe patent plan, the budget may be adjusted (e.g., a more superiorpatent position may require a larger budget). By conducting detailedexpense and growth estimation, a client can see the greater picture oftheir choices and goals (e.g., instead of looking at a patent budget ona yearly basis without strategic portfolio growth goals in mind). Withthis information, adequate funding can be secured and planning cancommence.

FIG. 163 is a diagram of an example of fees associated with patentprotecting an MTU as used by the improved computer for technology. FIG.163 shows legal service fees (e.g., U.S. attorney fees) and governmentfiling fees (e.g., U.S. government fees) for patent preparation andprosecution used to determine the patent preparation and prosecutionbudget of FIG. 162 .

The U.S. attorney fees data fields include a name of the service and therate, either fixed fee or hourly rate. Where hourly rates apply, anotherfield may include a type of practitioner (e.g., associate, partner,paralegal, etc.) and their corresponding billing rate. The serviceslisted include prepare and file a provisional application, prepare andfile a non-provisional application, prepare and file a legal placeholderinvention (LPI), prepare and file a PCT application, prepare and file acontinuation application, prepare and file a continuation-in-partapplication, prepare and file a divisional application, prepare and filea legal placeholder invention (LPI) conversion application, prepare andfile a provisional conversion application, prepare and file a designapplication, prepare and file an office action response, prepare andfile de minimus office action response, prepare and file restrictionresponse, issuance processing, annuity processing, maintenance feeprocessing, and portfolio management fee. More or less services mayexist depending upon the services offered. The hourly and/or fixed feesmay be entered by user input in accordance with a particular patentfirm's fee structure, automatically input based on average fees in aparticular region (e.g., the U.S.), and/or be set by default settings.

The U.S. government fees include a name of the item and the size of theentity that is filing the item (e.g., micro, small, or large, where thesize of the entity may dictate the fee). Government fee structures andentity classifications may vary in different countries. The names ofitems include a provisional application filing, a non-provisionalapplication filing, a PCT application filing, a design applicationfiling, an examination request, an issuance, annuities #1-#x (e.g.,depending on the year, country, etc.), and maintenance fees #1-#x (e.g.,depending on the year). The micro, small, and large fees may beautomatically and/or manually input based on the current fees charged bya government entity (e.g., the U.S. Patent Office). The new computer fortechnology is operable to continually update the fee structure and itemsin accordance with newly ingested data.

FIG. 164 is a logic diagram of an example of a method for balancingpatent spend and desired patent position for a plan to patent protect anMTU (market-tech unit) by a growth and expense co-processor of animproved computer for technology. In the method shown, the primarydriver in determining a patent preparation and prosecution plan is atotal patent budget from the patent plan (i.e., determining what patentportfolio is possible with a particular spend). The growth and expenseco-processor is operable to ingest hundreds to thousands of records andfactor in dozens of variables to determine detailed patent preparationand prosecution forecasting and expenses. Such processing is notoperable to be done solely by the human mind (e.g., it requiresartificial intelligence and/or a computer). The method begins with step1310 where a total patent budget regarding one or more time periods(e.g., 6 years) is determined from a patent plan. The total patentbudget is determined by a desired financial commitment and a desiredpatent position as discussed with reference to FIG. 162 .

The method continues with step 1312 where a patent plan domestic (e.g.,U.S.) to international spend ratio is determined. Determining the extentof international patent protection for technology is challenging. Thechallenge is balancing the cost of obtaining foreign national patentsand their business value with respect to obtaining U.S. patents andtheir business value. As in the U.S., desired use of patents and marketimpact of your patent protected technology drive the quantity and typesof patents to seek in other countries. While desired use of patents maybe the same domestically and internationally, in practice, the actualuses are quite different.

With respect to patent litigation, if a U.S. company can sue a potentialinfringer in the U.S. or in a foreign country, it will almost always suein the U.S. because it is much more costly to litigate a patentinfringement lawsuit in a foreign country as compared to the U.S.Further, it is far more convenient to file in the U.S. than in a foreigncountry by eliminating foreign travel and the need for foreign counsel.U.S. Courts are also much more likely to render an impartial decisionbased on patent laws than most other foreign courts.

For most multi-national companies, the U.S. accounts for a significantportion of their business. Thus, a U.S. patent portfolio providessubstantial leverage in coming to an acceptable resolution. Litigationis often used as pressure to execute a licensing agreement between theparties. As such, filing in the U.S. is a convenient and economicalapproach. With respect to licensing, a U.S. company typically determinesthe value of a licensing deal with a foreign company based on its U.S.patent portfolio and then increases a U.S. licensing rate by arelatively small amount (e.g., 0.5%) to establish a worldwide licensingrate.

With the actual uses being substantially different in the U.S. than inforeign countries for a U.S. company, it is beneficial to develop apatent portfolio to substantially favor U.S. patents over foreignnational patents. In essence, developing the U.S. portion of the patentportfolio creates market leverage and developing the foreigninternational of the patent portfolio provides strategic, additional,and/or alternative assertion, licensing, and/or partnering options. Fromthis philosophical viewpoint, an analytical approach is used toestablish the patent plan U.S. to international spend ratio.

The method continues with steps 1314 (for U.S. patent preparation andprosecution budget determination) and 1326 (for international patentpreparation and prosecution budget determination). At step 1314, the perperiod prosecution forecast is calculated. The per period prosecutionforecast is calculated based on the probability of the occurrence ofU.S. prosecution matters (e.g., office actions, appeal briefs,restriction responses, etc.) over a designated time period (e.g., aquarter, a year, 5 years, 7 years, etc.). For example, the probabilityof U.S. prosecution matters can be calculated for each filed applicationbased on the timeframe of prosecution matters (e.g., when an officeaction is likely to be received from the Patent Office) and how likelyvarious outcomes are (e.g., the probability of a first office actionallowance, etc.). Based on the probability of prosecution matters, anamount of prosecution matters can be estimated per period.

The method continues for U.S. patent preparation and prosecution budgetdetermination at step 1316 where the per period issuance forecast iscalculated. The per period issuance forecast is calculated based on thelikelihood of U.S. issuances in light of particular prosecution actionsper period. For example, the likelihood of an issuance due to a firstoffice action allowance may be lower than the likelihood of an issuancedue to a first office action response. Based on the probability ofissuances, an amount of issuances can be estimated per period.

The method continues for U.S. patent preparation and prosecution budgetdetermination at step 1318 where the per period maintenance forecast iscalculated. The per period maintenance forecast is calculated based onthe probability of issuances. For example, when a patent issues (basedon issuance forecasting), the occurrence of a maintenance fee can beestimated. Based on the probability of a maintenance fee, an amount ofmaintenance fees can be estimated per period.

The method continues for U.S. patent preparation and prosecution budgetdetermination at step 1320 where the per period subsequent filingforecast is calculated. The per period subsequent filing forecast iscalculated based on expected U.S. subsequent filings (e.g.,continuations, LPI conversion applications, divisional applications, andcontinuation-in-part applications) for the period. For example, when apatent issues (based on issuance forecasting), subsequent filings can beestimated based on a ratio of desired subsequent filings (e.g., theratio of continuations to divisional applications, etc.) and a filingfactor (e.g., a weight based on whether the subsequent filing isprimary, secondary, later). Based on the probability of subsequentfilings, a number of subsequent filings can be estimated per period.

The method continues for U.S. patent preparation and prosecution budgetdetermination at step 1322 where the per period number of newapplication filings is calculated. The per period number of newapplication filings is calculated based on anticipated and/or desirednew application filings (e.g., provisional applications andnon-provisional applications). The per period number of new applicationfilings may be determined based on a desired level of protection of theMTU involved, the desired patent position, available budget, a number ofinventions already identified, an amount of products in development,inventions typically obtained from advanced inventing sessions, etc.

The method continues for U.S. patent preparation and prosecution budgetdetermination at step 1324 where a new patent position is determinedbased on a new number of filings per period. For example, the growth andexpense co-processor calculates the probability of prosecution actions,issuances, maintenance fees, subsequent filings, and new filings andcalculates an estimated amount based on those probabilities. Based onthose amounts, a patent position is determined.

For international patent preparation and prosecution budgetdetermination, the method begins at step 1326 where a country to countryspend ratio is obtained and a per period PCT application filing forecastis determined. For example, one or more previously filed patentapplications and/or one or more new applications are selected for PCTapplication filing. For PCT applications approaching national stagedeadlines or applications to be filed directly in foreign countries,desired countries are selected (e.g., based on where competitors arelocated, where a large part of the market for a MTU exists, whereproducts are likely used, etc.). Based on the desired level of patentprotection in each of those countries and the cost of foreignpreparation and prosecution in those countries (e.g., some countries aremore costly than others), the country to country spend ratio isobtained.

The method continues for international patent preparation andprosecution budget determination at step 1328 where the per country, perperiod prosecution forecast is calculated. The per country, per periodprosecution forecast is calculated based on expected foreign prosecutionmatters (e.g., office actions, appeal briefs, restriction responses,etc.) for a designated time period (e.g., a quarter, a year, 5 years, 7years, etc.). For example, the probability of prosecution matters ineach country can be calculated for each application based on thetimeframe of prosecution matters (e.g., when an office action is likelyto be received from the country's patent office) and how likely variousoutcomes are (e.g., the probability of a first office action allowance,etc.). Based on the probability of prosecution matters, an amount ofprosecution matters can be estimated per period.

The method continues for international patent preparation andprosecution budget determination at step 1330 where a per country, perperiod issuance forecast is calculated. The per period issuance forecastis calculated based on the likelihood of foreign issuances in light ofparticular prosecution actions per period. For example, the likelihoodof an issuance due to a first office action allowance may be lower thanthe likelihood of an issuance due to a first office action response.Based on the probability of issuances, an amount of issuances can beestimated per period.

The method continues for international patent preparation andprosecution budget determination at step 1332 where per country, perperiod annuities forecast is calculated. The per country, per periodannuities forecast is calculated based on the probability of issuancesand the estimated length of prosecution. For example, when a patentissues (based on issuance forecasting), the occurrence of an annuity feecan be estimated. Further, in foreign countries, annuities may becharged to patent applicants during prosecution (e.g., on a yearlybasis). Based on the probability of an annuity fee, an amount of annuityfees can be estimated per period.

The method continues for international patent preparation andprosecution budget determination at step 1334 where the per country, perperiod subsequent filing forecast is calculated. The per country, perperiod subsequent filing forecast is calculated based on expectedsubsequent filings (e.g., continuations, divisional applications,continuation-in-part applications, etc.). For example, when a patentissues (based on issuance forecasting), subsequent filings can beestimated based on a ratio of desired subsequent filings (e.g., theratio of continuations to divisional applications, etc.) and a filingfactor (e.g., a weight based on whether the subsequent filing isprimary, secondary, later). Based on the probability of subsequentfilings, a number of subsequent filings can be estimated per period.

The method continues for international patent preparation andprosecution budget determination at step 1336 where the per country, perperiod number of new application filings is calculated. The per country,per period number of new application filings is calculated based onanticipated and/or desired new application filings for the period andthe corresponding fees (e.g., based on attorney fees and governmentfees) for each country. For example, the per country, per period numberof new application filings is calculated based on the number of perperiod number of new application filings filed in the U.S. (e.g., 5% ofnew U.S. applications are filed internationally). The method continuesfor international patent preparation and prosecution budgetdetermination at step 1338 where a per country, per period patentposition is determined based on the forecasting determined in steps1326-1336.

For example, the growth and expense co-processor calculates the percountry, per period probability of prosecution actions, issuances,annuities fees, subsequent filings, and new filings and calculates anestimated amount based on those probabilities. Based on the estimatedamounts, the per period, per country patent position can be determined.

When the U.S. patent position is calculated at step 1324, the methodcontinues with step 1340 where it is determined whether the U.S. budgetshould be adjusted. For example, the new patent position may be too weakand more funds are needed to reach a desired patent position.

When the per country patent position is calculated at step 1338, themethod continues with step 1340 where it is determined whether the percountry, per period and PCT international budget should be adjusted. Forexample, the calculated patent position may be too low to allow fordesired international patent protection in one or more country and morefunds need to be allocated to the international budget.

When it is determined that the U.S. or international budget should beadjusted, the method continues with step 1344 where it is determinedwhether the U.S. to international (“INT”) spend ratio should beadjusted. For example, if the calculated per period U.S. budget is toohigh in terms of the total patent budget from the patent plan, the U.S.to international spend ratio could be adjusted to allocate money fromthe international patent preparation and prosecution budget to the U.S.patent preparation and prosecution budget. If at step 1344 it isdetermined to adjust the U.S. to international spend ratio, the methodcontinues with step 1346 where the U.S. to international spend ratio isadjusted accordingly. When the international spend ratio is adjusted,the method branches back to step 1312 where the patent plan U.S. tointernational spend ratio is determined and used to determine the U.S.and international budgets.

If at step 1344, it is not determined to adjust the U.S. tointernational spend ratio, the method continues with step 1348 where itis determined whether the country to country ratio or the amount of PCTfilings should be adjusted. For example, when the patent position of oneor more country is too low, the country to country ratio can be adjustedto increase the amount of filings in the one or more country. As anotherexample, if U.S. patent portfolio growth is prioritized in a particularperiod over foreign portfolio growth, the per period PCT applicationfiling forecast can be scaled down. When it is determined that thecountry to country ratio and/or the amount of PCT filings should beadjusted, the method continues with step 1350 where the country tocountry ratio and/or the amount of PCT filings is adjusted accordingly.When the country to country ratio or the amount of PCT filings isadjusted, the method then branches to step 1326 where the country tocountry spend ratio and the per period PCT application filing forecastare obtained and determined to use in the international budget.

If the country to country ratio or the amount of PCT filings isdetermined to not be adjusted, the method continues with step 1352 whereforecast parameters are adjusted. Forecast parameters include theprobability of receiving office actions or issuances based on historicalor average data. Forecast parameters also include subsequent filingfactors (e.g., how many subsequent filings are likely per patentapplication), current portfolio matters (issued utility patents, pendingapplications, office actions, issuances, annuities/maintenance fees,prior art search/IDS, etc.), desired patent position, desired spend, andportfolio growth goals (number of desired new applications, etc.).

When the forecast parameters are adjusted at step 1352, the methodbranches back to step 1314 of the U.S. preparation and prosecutionbudget determination and/or step 1326 of the international preparationand prosecution budget determination. When it is determined that theU.S. or international patent position does not need to be adjusted, themethod continues with step 1342 where a report is generated. The reportmay include some or all of the forecasting information determined by thepresent method and well as budget information. To determine budgetinformation, the growth and expense co-processor calculates attorneyfees and government fees for each forecasted matter.

FIG. 165 is a diagram of an example of an input record regarding expenseand growth of patent protecting an MTU as used by a growth and expenseco-processor of an improved computer for technology. For example, theinput record includes inputs for expense and portfolio forecastingparameters per country when budget is driven by a particular spend. Datafields in blue are data input fields and data fields in gray includedata calculated by the growth and expense co-processor.

The expense and portfolio forecasting parameters per country in thisexample include the total annual patent budget, a total patent budgetcompound annual growth rate (CAGR), total annual patent budget for acurrent through sixth next period, a domestic (e.g., U.S.) percentage oftotal patent budget for a current through sixth next period, aninternational percentage of total patent budget for a current throughsixth next period, each foreign country's (e.g., country Σ throughcountry Ω) percentage of the international patent budget for a currentthrough sixth next period, and the probability of receiving actions forportfolio matter of office actions (OAs).

The total annual patent budget and a total patent budget CAGR are shownhere as data inputs (e.g., a user can set a desired amount). Based onthe total annual patent budget data input, the total annual patentbudget for a current through sixth next period can be calculated. Forexample, the life of a market-tech unit (MTU) can be used to allocatemore or less budget to certain periods.

The U.S. percentage of total patent budget for a current period is shownas a data input (e.g., based on a desired spend for U.S. portfoliogrowth and maintenance). Based on the percentage selected, the U.S.percentage of total patent budget for a first-sixth next period can becalculated. Because the U.S. percentage of total patent budget for acurrent period is a data input, the international percentage of totalpatent budget for the current through sixth next period is calculatedbased off of the total annual budget and the U.S. percentage of totalpatent budget.

Each selected country's percentage of the international percentage ofthe total patent budget for a current period is shown as a data input. Acertain country may be allocated more budget than another, when a higherlevel of patent protection is required in that country. Based on eachselected country's percentage of the international percentage of thetotal patent budget for the current period, each selected country'spercentage of the international percentage of the total patent budgetfor a current through sixth next period can be calculated.

The particular actions for portfolio matter of office actions showninclude a receive first office action allowance, a receive first officeaction, allowed after first office action response, allowed after secondoffice action response, allowed after third office action response,allowed after fourth office action response, a filing date to 1^(st)office action (OA) period of time (e.g., β), a first office actionwindow (e.g., σ), a time between subsequent office actions (e.g., δ),and a window of subsequent office actions (e.g., ε). Each of these datafields includes a calculated probability of action. The probabilities ofaction may be default settings or calculated based on past performanceand/or historical data.

FIG. 166 is a diagram of another example of an input record regardingexpense and growth of patent protecting an MTU as used by a growth andexpense co-processor of an improved computer for technology. The exampleinput record includes inputs for expense and portfolio forecastingparameters per country when budget is driven by desired spend. Datafields in blue are data input fields and data fields in gray includedata calculated by one or more processing modules of the new computerfor technology. Data input fields exist for existing quantities ofportfolio matters such as issued utility patents, pending provisionalapplications, pending non-provisional applications, pending PCTapplications, prior art (PA) searches/information disclosure statement(IDS), office actions, issuances, and annuities/maintenance fees.

The issuance actions include a first office action allowance, a receivefirst office action, a receive second office action, a receive thirdoffice action, a receive fourth office action, and a receive anotheroffice action. The receive probability of the issuance actions may bebased on default settings or calculated based on past performance. As anexample, the receive probability of a first office action allowance is5%, the receive probability of a first office action is 95%, the receiveprobability of a second office action is 31.64%, the receive probabilityof a third office action is 10.53%, the receive probability of a fourthoffice action is 3.51%, and the receive probability of another officeaction is 1.17%.

The allowance probabilities are shown as data input fields (with theexception of the first office action allowance probability) and may bebased on past performance or default settings. In this example, thefirst office action allowance probability is 100% and the rest of theissuance actions have a 66.7% chance of resulting in allowance. A perpatent issuance probability is calculated by multiplying the receiveprobability by the allowance probability. For example, the issuanceprobability of a first office action allowance is 5% (e.g., 5%×100%),the issuance probability of a first office action is 63.4% (e.g.,95%×66.7%), the issuance probability of a second office action is 21.1%(e.g., 31.64%×66.7%), the issuance probability of a third office actionis 7.0% (e.g., 10.53%×66.7%), the issuance probability of a fourthoffice action is 2.3% (e.g., 3.51%×66.7%), and the issuance probabilityof another office action is 0.8% (e.g., 1.17%×66.7%).

Further data input fields exist for subsequent filing factors. Thesubsequent filing factors may be default settings. Here, there are datainput fields for a primary subsequent filing (e.g., after a firstissuance) and a secondary subsequent filing (e.g., second issuance andbeyond) but more or less are possible. In this example, for a primarysubsequent filing, there is a subsequent filing factor of 1.25, acontinuation factor of 15%, a divisional factor of 2.5%, a CIP factor of7.5%, and a legal placeholder conversion (LPC) (also referred to hereinas an LPI conversion application) factor of 75%. For a secondarysubsequent filing there is a subsequent filing factor of 0.5%, acontinuation factor of 50%, a divisional factor of 5%, a CIP factor of20%, and an LPC factor of 25%. The factors may be default settings orcalculated based on past performance or particular portfolio goals(e.g., the portfolio may lean heavily toward bundled applications andrequire more LPC subsequent application filings).

FIG. 167 is a logic diagram of another example of a method for balancingpatent spend and desired patent position for a plan to patent protect anMTU (market-tech unit) by a growth and expense co-processor of animproved computer for technology. In the method of FIG. 167 , theprimary driver is a desired patent position (i.e., number of filings perthe patent plan). The method begins with step 1360 where a desiredpatent position is obtained for one or more periods. The desired patentposition may be sliding scale from weak to superior (e.g., a numericalscale where 1 is weak and 10 is superior). A superior patent position isachieved by creating a patent portfolio that is balanced, has broadtechnology boundaries, and has no weaknesses. As such, a medium patentposition is less balanced, has less broad technology boundaries, and hasmore weaknesses than a superior patent position and a weak patentposition is not balanced, has narrow technology boundaries, and has manyweaknesses.

The method continues with step 1362 where a desired patent position isdetermined for domestic (e.g., the U.S.) and international patentprotection. For example, prioritizing the development of a U.S. patentportfolio may indicate a desired patent position for the U.S. to besuperior whereas the desired patent position for international ismedium.

The method continues with steps 1364 (for U.S. patent preparation andprosecution budget determination) and 1376 (for international patentpreparation and prosecution budget determination). At step 1364, the perperiod number of new application filings is determined. The per periodnumber of new application filings (e.g., provisional applications andnon-provisional applications) is determined based on the desired patentposition for a period (e.g., a quarter, a year, 5 years, 7 years, etc.).For example, a superior patent position may require a higher number ofnew application filings than a less superior patent position.

The method continues for U.S. patent preparation and prosecution budgetdetermination at step 1366 where the per period prosecution forecast isdetermined. The per period prosecution forecast is calculated based onthe probability of the occurrence of U.S. prosecution matters (e.g.,office actions, appeal briefs, restriction responses, etc.) over adesignated time period (e.g., a quarter, a year, 5 years, 7 years,etc.). For example, the probability of U.S. prosecution matters can becalculated for each filed application based on the timeframe ofprosecution matters (e.g., when an office action is likely to bereceived from the Patent Office) and how likely various outcomes are(e.g., the probability of a first office action allowance, etc.). Basedon the probability of prosecution matters, an amount of prosecutionmatters can be estimated per period.

The method continues for U.S. patent preparation and prosecution budgetdetermination at step 1368 where the per period issuance forecast isdetermined. The per period issuance forecast is calculated based on thelikelihood of U.S. issuances in light of particular prosecution actionsper period. For example, the likelihood of an issuance due to a firstoffice action allowance may be lower than the likelihood of an issuancedue to a first office action response. Based on the probability ofissuances, an amount of issuances can be estimated per period.

The method continues for U.S. patent preparation and prosecution budgetdetermination at step 1370 where the per period maintenance forecast isdetermined. The per period maintenance forecast is calculated based onthe probability of issuances. For example, when a patent issues (basedon issuance forecasting), the occurrence of a maintenance fee can beestimated. Based on the probability of a maintenance fee, an amount ofmaintenance fees can be estimated per period.

The method continues for U.S. patent preparation and prosecution budgetdetermination at step 1372 where the per period subsequent filingforecast is calculated. The per period subsequent filing forecast iscalculated based on expected U.S. subsequent filings (e.g.,continuations, LPI conversion applications, divisional applications, andcontinuation-in-part applications) for the period. For example, when apatent issues (based on issuance forecasting), subsequent filings can beestimated based on a ratio of desired subsequent filings (e.g., theratio of continuations to divisional applications, etc.) and a filingfactor (e.g., a weight based on whether the subsequent filing isprimary, secondary, later). Based on the probability of subsequentfilings, a number of subsequent filings can be estimated per period.

The method continues for U.S. patent preparation and prosecution budgetdetermination at step 1374 where a per period U.S. budget is determinedbased on the forecasting determined in steps 1364-1374. For example, thegrowth and expense co-processor calculates the an amount of new filingsand the probability of prosecution actions, issuances, maintenance fees,and subsequent filings, and calculates estimated amounts based on thoseprobabilities. Based on the estimated amounts, the growth and expenseco-processor calculates the attorney fees and government fees associatedwith each item and compiles the expenses into a total per period budget.

For international patent preparation and prosecution budgetdetermination, the method begins at step 1376 where a country to countrypatent position is determined and a per period PCT application filingforecast is determined. For example, one or more previously filed patentapplications and/or one or more new applications are selected for PCTapplication filing. For PCT applications already filed and approachingnational stage deadlines or applications to be filed directly in foreigncountries, desired countries are selected (e.g., where competitors arelocated, where a large part of the market for an MTU exists, whereproducts are likely used, etc.). Based on the desired level of patentprotection in each of those countries, the per country patent positionis determined.

The method continues for international patent preparation andprosecution budget determination at step 1378 where the per country, perperiod (e.g., a quarter, a year, 5 years, 7 years, etc.) number of newapplication filings is determined. The per country, per period number ofnew application filings is determined based on anticipated and/ordesired new application filings in accordance with a desired patentposition for the period for each country.

The method continues for international patent preparation andprosecution budget determination at step 1380 where the per country, perperiod prosecution forecast is calculated. The per country, per periodprosecution forecast is calculated based on expected foreign prosecutionmatters (e.g., office actions, appeal briefs, restriction responses,etc.) for a designated time period (e.g., a quarter, a year, 5 years, 7years, etc.). For example, the probability of prosecution matters ineach country can be calculated for each application based on thetimeframe of prosecution matters (e.g., when an office action is likelyto be received from the country's patent office) and how likely variousoutcomes are (e.g., the probability of a first office action allowance,etc.). Based on the probability of prosecution matters, an amount ofprosecution matters can be estimated per period.

The method continues for international patent preparation andprosecution budget determination at step 1382 where a per country, perperiod issuance forecast is determined. The per period issuance forecastis calculated based on the likelihood of foreign issuances in light ofparticular prosecution actions per period. For example, the likelihoodof an issuance due to a first office action allowance may be lower thanthe likelihood of an issuance due to a first office action response.Based on the probability of issuances, an amount of issuances can beestimated per period.

The method continues for international patent preparation andprosecution budget determination at step 1384 where per country, perperiod annuities forecast is calculated. The per country, per periodannuities forecast is calculated based on the probability of issuancesand the estimated length of prosecution. For example, when a patentissues (based on issuance forecasting), the occurrence of an annuity feecan be estimated. Further, in foreign countries, annuities may becharged to patent applicants during prosecution (e.g., on a yearlybasis). Based on the probability of an annuity fee, an amount of annuityfees can be estimated per period.

The method continues for international patent preparation andprosecution budget determination at step 1386 where the per country, perperiod subsequent filing forecast is calculated. The per country, perperiod subsequent filing forecast is calculated based on expectedsubsequent filings (e.g., continuations, divisional applications,continuation-in-part applications, etc.). For example, when a patentissues (based on issuance forecasting), subsequent filings can beestimated based on a ratio of desired subsequent filings (e.g., theratio of continuations to divisional applications, etc.) and a filingfactor (e.g., a weight based on whether the subsequent filing isprimary, secondary, later). Based on the probability of subsequentfilings, a number of subsequent filings can be estimated per period.

The method continues for international patent preparation andprosecution budget determination at step 1388 where a per country, perperiod and PCT filing international budget is determined based onforecasting determined in steps 1376-1386. For example, the growth andexpense co-processor calculates the per country, per period probabilityof prosecution actions, issuances, annuities fees, subsequent filings,in accordance with projected new filings and calculates estimatedamounts based on those probabilities. Based on the estimated amounts,the growth and expense co-processor calculates the attorney fees andgovernment fees associated with each item and compiles the expenses intoa total per period, per country budget.

When the U.S. patent preparation and prosecution budget is calculated atstep 1374, the method continues with step 1390 where it is determinedwhether the per period U.S. budget should be adjusted. For example, thecalculated per period U.S. budget may be too expensive. When theinternational patent preparation and prosecution budget is calculated atstep 1388, the method continues with step 1390 where it is determinedwhether the per country, per period and PCT international budget shouldbe adjusted. For example, the calculated per country, per period and PCTinternational budget may be too high or too low to allow for desiredinternational patent protection.

When it is determined that the U.S. or international budget should beadjusted, the method continues with step 1394 where it is determinedwhether the U.S. or international (“INT”) patent position should beadjusted. For example, if the calculated per period U.S. budget is toohigh, the U.S. desired patent position may be lowered. If at step 1394it is determined to adjust the U.S. or international patent position,the method continues with step 1396 where the U.S. or internationaldesired patent position is adjusted accordingly. When the desired patentposition is adjusted accordingly, the method branches back to step 1362where the patent position of U.S. and international patent protection isdetermined.

If at step 1394 it is not determined to adjust the U.S. or internationalpatent position, the method continues with step 1398 where it isdetermined whether the country position or the amount of PCT filingsshould be adjusted. For example, when the international budget is toohigh, the country position for one or more countries can be lowered toreduce the amount of filings and cost. As another example, if U.S.patent portfolio growth is prioritized in a particular period overforeign portfolio growth, the per period PCT application filing forecastcan be scaled down. When it is determined that the country position orthe amount of PCT filings should be adjusted, the method continues withstep 1402 where the country position and/or the amount of PCT filings isadjusted accordingly. When the country position and/or the amount of PCTfilings is adjusted accordingly, the method then branches to step 1376where the country position and the per period PCT application filingforecast are determined.

If the country position or the amount of PCT filings is determined tonot be adjusted, the method continues with step 1400 where forecastparameters are adjusted. Forecast parameters include the probability ofreceiving office actions or issuances based on historical or averagedata. Forecast parameters also include subsequent filing factors (e.g.,how many subsequent filings are likely per patent application), currentportfolio matters (issued utility patents, pending applications, officeactions, issuances, annuities/maintenance fees, prior art search/IDS,etc.), and portfolio growth goals (number of desired new applications,etc.).

When the forecast parameters are adjusted at step 1400, the methodbranches back to step 1364 of the U.S. preparation and prosecutionbudget determination and/or step 1376 of the international preparationand prosecution budget determination. When it is determined that theU.S. or international budget should not be adjusted, the methodcontinues with step 1392 where a report is generated. The report mayinclude some or all of the forecasting and budget information determinedby the present method.

FIG. 168 is a diagram of another example of an input record regardingexpense and growth of patent protecting an MTU as used by a growth andexpense co-processor of an improved computer for technology. The inputrecord of FIG. 168 includes inputs for expense and portfolio forecastingparameters per country when budget is driven by new application filingnumbers (e.g., a desired patent position). Data fields exist forexisting quantities of portfolio matters (e.g., from a private patentdatabase) such as quantities of issued utility patents, pendingprovisional applications, pending non-provisional applications, pendingPCT applications, prior art (PA) searches/information disclosurestatement (IDS), office actions, issuances, and annuities/maintenancefees. New filings are forecasted based on data from a private patentdatabase (e.g., advanced inventing session data) and from a patent plan(e.g., a desired patent position).

The portfolio matters for new filings include, for example, newprovisional filings, new utility filings, new PCT filings, and newdesign filings. More or less portfolio matters may exist. A currentperiod (CP) quantity (e.g., a goal for the current year) for each of theportfolio matters can be inputted or calculated based on patent planobjectives. Additionally, first next period (NP) (e.g., next year)through sixth NP (e.g., six years from now) quantities for each of theportfolio matters can be inputted or calculated based on patent planobjectives and quantities of previous periods. More or less periods thanshown may be included.

The particular actions for portfolio matter of office actions showninclude a receive first office action allowance, a receive first officeaction, allowed after first office action response, allowed after secondoffice action response, allowed after third office action response,allowed after fourth office action response, a filing date to 1^(st)office action (OA) period of time (e.g., β), a first office actionwindow (e.g., σ), a time between subsequent office actions (e.g., δ),and a window of subsequent office actions (e.g., ε). Each of these datafields includes a calculated or inputted probability of action. Theprobabilities of action may be default settings or calculated based onpast performance and/or historical data.

FIG. 169 is a diagram of another example of an input record regardingexpense and growth of patent protecting an MTU as used by a growth andexpense co-processor of an improved computer for technology. The inputrecord of FIG. 169 includes inputs for expense and portfolio forecastingparameters per country when budget is driven by filing numbers (e.g.,based on a desired patent position). Data fields in blue are data inputfields and data fields in gray include data calculated by one or moreprocessing modules of the new computer for technology.

The issuance actions include a first office action allowance, a receivefirst office action, a receive second office action, a receive thirdoffice action, a receive fourth office action, and a receive anotheroffice action. The receive probability of the issuance actions may bebased on default settings or calculated based on past performance. As anexample, the receive probability of a first office action allowance is5%, the receive probability of a first office action is 95%, the receiveprobability of a second office action is 31.64%, the receive probabilityof a third office action is 10.53%, the receive probability of a fourthoffice action is 3.51%, and the receive probability of another officeaction is 1.17%.

The allowance probabilities are shown as data input fields (with theexception of the first office action allowance probability) and may bedefault settings or calculated based on past performance. In thisexample, the first office action allowance probability is 100% and therest of the issuance actions have a 66.7% chance of resulting inallowance. A per patent issuance probability is calculated bymultiplying the receive probability by the allowance probability. Forexample, the issuance probability of a first office action allowance is5.0% (e.g., 5.0%×100%), the issuance probability of a first officeaction is 63.4% (e.g., 95%×66.7%), the issuance probability of a secondoffice action is 21.1% (e.g., 31.64%×66.7%), the issuance probability ofa third office action is 7.0% (e.g., 10.53%×66.7%), the issuanceprobability of a fourth office action is 2.3% (e.g., 3.51%×66.7%), andthe issuance probability of another office action is 0.8% (e.g.,1.17%×66.7%).

Further data input fields exist for subsequent filing factors. Thesubsequent filing factors may be default settings, calculated based onpast performance, and/or determined based on portfolio goals. Here,there are data input fields for a primary subsequent filing (e.g., aftera first issuance) and a secondary subsequent filing (e.g., secondissuance and beyond) but more or less are possible. In this example, fora primary subsequent filing, there is a subsequent filing factor andfactors (percentages) for each type of subsequent filing.

The subsequent filing factor is a weight applied to the varioussubsequent filing percentages based on how desired the filing is. Forthe primary subsequent filing, the subsequent filing factor is 1.25, thecontinuation factor is 15%, the divisional factor is 2.5%, the CIPfactor is 7.5%, and the legal placeholder conversion (LPC) (alsoreferred to herein as an LPI conversion application) factor is 75%. Fora secondary subsequent filing there is a subsequent filing factor of0.5, a continuation factor of 50%, a divisional factor of 5%, a CIPfactor of 20%, and an LPC factor of 25%.

FIG. 170 is a diagram of an example of a multi-period expense and growthestimation of patent protecting an MTU that compounds over time. Themulti-period expense and growth estimation includes an existing periodand forecasting for a current period (CP), a first next period (1NP), asecond next period (2NP), a third next period (3NP), a fourth nextperiod (4NP), a fifth next period (5NP), and a sixth next period (6NP).In this example, portfolio matters are forecasted on a yearly basis(e.g., a period is one year) but other time periods (e.g., quarterly,bi-annually, etc.) are possible. The Existing portfolio matters exist atan “existing” time period and are maintained and prosecuted throughoutportfolio development (e.g., from the existing time to the sixth nextperiod). The multi-period expense and growth estimation includes acurrent period (CP) forecast (e.g., for a current year) to map outcurrent period portfolio matters. As shown, during the current period,the multi-period expense and growth estimation includes existingportfolio matters and current period portfolio matters and a runningtotal.

The multi-period expense and growth estimation includes a first nextperiod (1NP) forecast (e.g., for first next year) to map out first nextperiod portfolio matters. During the first next period, the multi-periodexpense and growth estimation includes existing, current, and first nextperiod portfolio matters and a running total. The multi-period expenseand growth estimation includes a second next period (2NP) forecast(e.g., for a second next year) to map out second next period portfoliomatters. During the second next period, the multi-period expense andgrowth estimation includes existing, current, first, and second nextperiod portfolio matters and a running total.

The multi-period expense and growth estimation includes a third nextperiod (3NP) forecast (e.g., for a third next year) to map out thirdnext period portfolio matters. During the third next period, themulti-period expense and growth estimation includes existing, current,first, second, and third next period portfolio matters and a runningtotal. The multi-period expense and growth estimation includes a fourthnext period (4NP) forecast (e.g., for a fourth next year) to map outfourth next period portfolio matters. During the fourth next period, themulti-period expense and growth estimation includes existing, current,first, second, third, and fourth next period portfolio matters and arunning total.

The multi-period expense and growth estimation includes a fifth nextperiod (5NP) forecast (e.g., for a fifth next year) to map out fifthnext period portfolio matters. During the fifth next period, themulti-period expense and growth estimation includes existing, current,first, second, third, fourth, and fifth next period portfolio mattersand a running total. The multi-period expense and growth estimationincludes a sixth next period (6NP) forecast (e.g., for a sixth nextyear) to map out sixth next period portfolio matters. During the sixthnext period, the multi-period expense and growth estimation includesexisting, current, first, second, third, fourth, fifth, and sixth nextperiod portfolio matters and a running total. The multi-period expenseand growth estimation may go further into the future or show lessperiods than this example.

By forecasting portfolio matters for multiple periods, the portfoliosize, strength, and budget can be analyzed and strategized in accordancewith desired patent position and patent business goals.

FIG. 171 is a diagram of an example of a multiple time periodsrelationship to each other as time passes regarding expense and growthestimation of patent protecting an MTU. For example, FIG. 171 showsexpense and growth estimation that forecasts portfolio matters on ayearly basis (e.g., each period is one year) for a current period (CP),a first next period (1NP), a second next period (2NP), a third nextperiod (3NP), a fourth next period (4NP), a fifth next period (5NP), anda sixth next period (6NP) over the course of five years. Longer orshorter periods are possible.

In a first year, the current period (CP) is 1/1/2022-12/31/2022, thefirst next period (1NP) is the next year 1/1/2023-12/31/2023, the secondnext period (2NP) is the next year 1/1/2024-12/31/2024, the third nextperiod (3NP) is the next year 1/1/2025-12/31/2025, the fourth nextperiod (4NP) is the next year 1/1/2026-12/31/2026, the fifth next period(5NP) is the next year 1/1/2027-12/31/2027, and the sixth next period(6NP) is the next year 1/1/2028-12/31/2028.

As time moves on to the second year, the first next period (1NP) of1/1/2023-12/31/2023 from above becomes the current period, the firstnext period (1NP) is the next year 1/1/2024-12/31/2024, the second nextperiod (2NP) is the next year 1/1/2025-12/31/2025, the third next period(3NP) is the next year 1/1/2026-12/31/2026, the fourth next period (4NP)is the next year 1/1/2027-12/31/2027, the fifth next period (5NP) is thenext year 1/1/2028-12/31/2028, and the sixth next period (6NP) is thenext year 1/1/2029-12/31/2029.

As time moves on to the third year, the first next period (1NP) of1/1/2024-12/31/2024 from above becomes the current period, the firstnext period (1NP) is the next year 1/1/2025-12/31/2025, the second nextperiod (2NP) is the next year 1/1/2026-12/31/2026, the third next period(3NP) is the next year 1/1/2027-12/31/2027, the fourth next period (4NP)is the next year 1/1/2028-12/31/2028, the fifth next period (5NP) is thenext year 1/1/2029-12/31/2029, and the sixth next period (6NP) is thenext year 1/1/2030-12/31/2030.

As time moves on to the fourth year, the first next period (1NP) of1/1/2025-12/31/2025 from above becomes the current period, the firstnext period (1NP) is the next year 1/1/2026-12/31/2026, the second nextperiod (2NP) is the next year 1/1/2027-12/31/2027, the third next period(3NP) is the next year 1/1/2028-12/31/2028, the fourth next period (4NP)is the next year 1/1/2029-12/31/2029, the fifth next period (5NP) is thenext year 1/1/2030-12/31/2030, and the sixth next period (6NP) is thenext year 1/1/2031-12/31/2031.

As time moves on to the fifth year, the first next period (1NP) of1/1/2026-12/31/2026 from above becomes the current period, the firstnext period (1NP) is the next year 1/1/2027-12/31/2027, the second nextperiod (2NP) is the next year 1/1/2028-12/31/2028, the third next period(3NP) is the next year 1/1/2029-12/31/2029, the fourth next period (4NP)is the next year 1/1/2030-12/31/2030, the fifth next period (5NP) is thenext year 1/1/2031-12/31/2031, and the sixth next period (6NP) is thenext year 1/1/2032-12/31/2032.

FIG. 172 is a diagram of an example of a growth forecast recordregarding patent protecting an MTU as used by a growth and expenseco-processor of an improved computer for technology. The growth forecastrecord includes actual (e.g., existing) and forecasted quantities ofportfolio matter for periods of time (e.g., year-by-year) of a patentplan. Data fields in blue are data input fields, data fields in lightgray include data calculated by one or more processing modules of thenew computer for technology, and data fields in dark gray are datalookup fields. The year-by-year totals could be per country and/orcombined for all countries involved. A separate, similar analysis canoccur for design patents. While quantities are shown here, the totalspend can also be tracked.

The portfolio matters listed include issued utility patents, pendingprovisional applications, pending non-provisional applications, pendingPCT applications, new provisional filings, new utility filings, new PCTfilings, provisional conversions, PCT conversions, new continuation(CON) filings, new divisional (DIV) filings, new continuation-in-part(CIP) filings, new legal placeholder conversion (LPC) filings, prior art(PA) search/information disclosure statement (IDS), office actions(e.g., including appeal briefs, reply briefs, petitions, etc., andfactoring requests for continued examination (RCE)), issuances, andannuities/maintenance fees. Actions for portfolio matters may includefiling new applications, responses to office actions, etc.

The actual portfolio matters in the growth forecast record includeexisting quantities of issued utility patents, pending provisionalapplications, pending non-provisional applications, pending PCTapplications, prior art (PA) search/information disclosure statement(IDS), office actions, issuances, and annuities/maintenance fees. Theexisting quantities of actual portfolio matters may be included via adata lookup.

The forecasted portfolio matters in the growth forecast record includeforecasted quantities for each portfolio matter for a current period(CP), a first next period (1NP), a second next period (2NP), a thirdnext period (3NP), a fourth next period (4NP), a fifth next period(5NP), and a sixth next period (6NP). More or less periods forforecasting are possible. Quantities for new application filings such asnew provisional filings, new utility filings, and new PCT filings can beinput based on a desired patent position. Other forecasted portfoliomatters can be calculated by the growth and expense co-processor basedon new filings, budget, past performance, desired patent position,and/or default settings.

FIG. 173 is a diagram of another example of a growth forecast recordregarding patent protecting an MTU as used by a growth and expenseco-processor of an improved computer for technology. The forecastingestimations included in the growth forecast record may be based on pastperformance, statistical data, default settings, forecasting parameters,desired patent position, etc. The quantities may be broken down percountry or combined for multiple countries. The quantities may be brokendown per market-tech unit (MTU) or combined. In this example, theportfolio matters shown include yearly quantities of inventionsdisclosed, inventions protected, pending provisional applications,pending non-provisional applications, pending PCT applications, andissued patents. Disclosed inventions are inventions that have beendisclosed to the patent process but not yet included in a patentapplication. Protected inventions are inventions that are included in anapplication, either claimed out or included as legal placeholderinventions (LPIs).

In this example, for the actual (e.g., existing) portfolio matters,there are 24 existing inventions disclosed, 24 inventions protected, 0pending provisional applications, 6 pending non-provisionalapplications, 0 pending PCT applications, and 0 issued patents. Forexample, the existing portfolio includes six utility patent applicationshaving four inventions each as well as 24 inventions that have yet to beincluded in an application. For a current period (CP) (e.g., a currentyear), it is forecasted that there will be 24 inventions disclosed, 24inventions protected, 0 pending provisional applications, 24 pendingnon-provisional applications, 0 pending PCT applications, and 6 issuedpatents for that period. For example, during the current period, thepreviously disclosed 24 inventions are filed as six new utility patentapplications each having four inventions. It is estimated that 18subsequent filings will occur in the current period (e.g., LPCs,continuations, etc.). With 6 issuances, 6 previously filed applications,6 new applications, and 18 subsequent filings, the total quantity ofpending non-provisional applications is 24 (6 +6 +18-6) during thecurrent period.

For a first next period (1NP) (e.g., a next year), it is forecasted thatthere will be 24 inventions disclosed, 24 inventions protected, 0pending provisional applications, 33 pending non-provisionalapplications, 0 pending PCT applications, and 15 issued patents for thatperiod. For example, during the first next period, the previouslydisclosed 24 inventions are filed as six new utility patent applicationseach having four inventions. It is estimated that 18 subsequent filingswill occur in the current period (e.g., LPCs, continuations, etc.). With15 issuances, 6 prior issuances, 30 previously filed applications, 6 newapplications, and 18 subsequent filings, the total quantity of pendingnon-provisional applications is 33 during the first next period.

For a second next period (2NP) (e.g., a second next year), it isforecasted that there will be 24 inventions disclosed, 24 inventionsprotected, 0 pending provisional applications, 32 pendingnon-provisional applications, 0 pending PCT applications, and 25 issuedpatents for that period. For example, during the second next period, thepreviously disclosed 24 inventions are filed as six new utility patentapplications each having four inventions. It is estimated that 18subsequent filings will occur in the current period (e.g., LPCs,continuations, etc.). With 25 issuances, 21 prior issuances, 54previously filed applications, 6 new applications, and 18 subsequentfilings, the total quantity of pending non-provisional applications is32 during the second next period.

For a third next period (3NP) (e.g., a third next year), it isforecasted that there will be 24 inventions disclosed, 24 inventionsprotected, 0 pending provisional applications, 26 pendingnon-provisional applications, 0 pending PCT applications, and 30 issuedpatents for that period. For example, during the third next period, thepreviously disclosed 24 inventions are filed as six new utility patentapplications each having four inventions. It is estimated that 18subsequent filings will occur in the current period (e.g., LPCs,continuations, etc.). With 30 issuances, 46 prior issuances, 78previously filed applications, 6 new applications, and 18 subsequentfilings, the total quantity of pending non-provisional applications is26 during the third next period.

For a fourth next period (4NP) (e.g., a fourth next year), it isforecasted that there will be 24 inventions disclosed, 24 inventionsprotected, 0 pending provisional applications, 18 pendingnon-provisional applications, 0 pending PCT applications, and 32 issuedpatents for that period. For example, during the fourth next period, thepreviously disclosed 24 inventions are filed as six new utility patentapplications each having four inventions. It is estimated that 18subsequent filings will occur in the current period (e.g., LPCs,continuations, etc.). With 32 issuances, 76 prior issuances, 102previously filed applications, 6 new applications, and 18 subsequentfilings, the total quantity of pending non-provisional applications is18 during the fourth next period.

For a fifth next period (5NP) (e.g., a fifth next year), it isforecasted that there will be 24 inventions disclosed, 24 inventionsprotected, 0 pending provisional applications, 7 pending non-provisionalapplications, 0 pending PCT applications, and 35 issued patents for thatperiod. For example, during the fifth next period, the previouslydisclosed 24 inventions are filed as six new utility patent applicationseach having four inventions. It is estimated that 18 subsequent filingswill occur in the current period (e.g., LPCs, continuations, etc.). With35 issuances, 108 prior issuances, 126 previously filed applications, 6new applications, and 18 subsequent filings, the total quantity ofpending non-provisional applications is 7 during the fifth next period.

For a sixth next period (6NP) (e.g., a sixth next year), it isforecasted that there will be 0 inventions disclosed, 24 inventionsprotected, 0 pending provisional applications, 11 pendingnon-provisional applications, 0 pending PCT applications, and 20 issuedpatents for that period. For example, during the sixth next period, thepreviously disclosed 24 inventions are filed as six new utility patentapplications each having four inventions. It is estimated that 18subsequent filings will occur in the current period (e.g., LPCs,continuations, etc.). With 20 issuances, 143 prior issuances, 150previously filed applications, 6 new applications, and 18 subsequentfilings, the total quantity of pending non-provisional applications is11 during the sixth next period.

FIG. 174 is a diagram of another example of a growth forecast recordregarding patent protecting an MTU as used by a growth and expenseco-processor of an improved computer for technology. The example of FIG.174 is similar to the example of FIG. 173 except that running totals forportfolio matters are shown.

For the actual portfolio matters, there are 24 existing inventionsdisclosed, 24 inventions protected, 0 pending provisional applications,6 pending non-provisional applications, 0 pending PCT applications, and0 issued patents. For a current period (CP) (e.g., a current year), itis forecasted that there will be 24 inventions disclosed making arunning total of 48 disclosed inventions, a running total of 48inventions protected, 0 pending provisional applications, 24 pendingnon-provisional applications, 0 pending PCT applications, and 6 issuedpatents.

For a first next period (1NP) (e.g., a next year), it is forecasted thatthere will be 24 inventions disclosed making a running total of 72disclosed inventions, a running total of 72 inventions protected, 0pending provisional applications, 33 pending non-provisionalapplications, 0 pending PCT applications, and a running total of 21issued patents. For a second next period (2NP) (e.g., a second nextyear), it is forecasted that there will be 24 inventions disclosedmaking a running total of 96 disclosed inventions, a running total of 96inventions protected, 0 pending provisional applications, 32 pendingnon-provisional applications, 0 pending PCT applications, and a runningtotal of 46 issued patents.

For a third next period (3NP) (e.g., a third next year), it isforecasted that there will be 24 inventions disclosed making a runningtotal of 120 disclosed inventions, a running total of 120 inventionsprotected, 0 pending provisional applications, 26 pendingnon-provisional applications, 0 pending PCT applications, and a runningtotal of 76 issued patents.

For a fourth next period (4NP) (e.g., a fourth next year), it isforecasted that there will be 24 inventions disclosed making a runningtotal of 144 disclosed inventions, a running total of 144 inventionsprotected, 0 pending provisional applications, 18 pendingnon-provisional applications, 0 pending PCT applications, and a runningtotal of 108 issued patents.

For a fifth next period (5NP) (e.g., a fifth next year), it isforecasted that there will be 24 inventions disclosed making a runningtotal of 168 disclosed inventions, a running total of 168 inventionsprotected, 0 pending provisional applications, 7 pending non-provisionalapplications, 0 pending PCT applications, and a running total of 143issued patents. For a sixth next period (6NP) (e.g., a sixth next year),it is forecasted that there will be 0 inventions disclosed making arunning total of 168 disclosed inventions, a running total of 192inventions protected, 0 pending provisional applications, 11 pendingnon-provisional applications, 0 pending PCT applications, and a runningtotal of 163 issued patents for that period.

FIG. 175 is a logic diagram of an example of a method for forecastingupcoming actions regarding patent protecting an MTU (market-tech unit)based on existing patent protected inventions by a growth and expenseco-processor of an improved computer for technology. The method beginswith step 1410 where the growth and expense co-processor determinesexisting portfolio matters are determined. Existing portfolio mattersinclude filed provisional and/or non-provisional applications, filed PCTapplications, filed subsequent filings, issuances, filed office actionsresponses, maintenance fees paid, etc. The growth and expenseco-processor may perform a data lookup to determine the existingportfolio matters.

The method continues with step 1412 where the growth and expenseco-processor determines upcoming actions based on the existing portfoliomatters. For example, if a non-provisional application has been filed,responses to office actions and/or an issuance are upcoming. An amountof subsequent filings (e.g., continuations, LPCs, continuations-in-part,etc.) based off the non-provisional application can also be estimated.In another example, if an issuance occurred, an upcoming action mayinclude paying maintenance fees.

The method continues with step 1414 where the growth and expenseco-processor identifies upcoming actions based on the existing portfoliomatters that occur in a current period. A period may be set as anylength of time that makes sense for a business and/or a technology. Forexample, the period may be a year taking into account most businessesbudget and plan for the current year. Other time periods such as aquarter or two years are also possible. In the example of an existingnon-provisional application, a first office action response or firstoffice action allowance may be expected in the current period.

The method continues with step 1416 where the growth and expenseco-processor identifies upcoming actions that occur in a first nextperiod. The upcoming actions in a first next period are identified basedon the existing portfolio matters and a likely outcome of actions thatoccurred in the current period. In an example of an existingnon-provisional application where a first office action response waslikely filed in a current period, in the first next period a secondoffice action response and a request for continued examination may beexpected. Further, filing a certain number of subsequent filings off ofthe non-provisional application may be expected in the first nextperiod.

The method continues with step 1418 where upcoming actions that occur ina second next period are identified. The upcoming actions in a secondnext period are identified based on the existing portfolio matters and alikely outcome of actions that occurred in the current and first nextperiods. In an example of an existing non-provisional application wherea first office action response was likely filed in a current period anda second office action response with a request for continued examinationwas likely filed in the first next period, in the second next period afirst office action response after request for continued examination maybe expected. Further, with subsequent filings that were filed in thefirst next period, an amount of office action responses related to thosefilings may be expected in the second next period.

The method continues with step 1420 where the growth and expenseco-processor identifies upcoming actions that occur in a third nextperiod. The upcoming actions in a third next period are identified basedon the existing portfolio matters and a likely outcome of actions thatoccurred in the current, first next, and second next periods. In anexample of an existing non-provisional application where a first officeaction response was likely filed in a current period, a second officeaction response with a request for continued examination was likelyfiled in the first next period, and a first office action response afterrequest for continued examination was likely filed in the second nextperiod, in the third next period an issuance may be expected. With theissuance, a subsequent filing such as a continuation may also beexpected. Further, with subsequent filings that were filed in the firstnext period and office action responses related to those filingsexpected in the second next period, additional office action responsesand/or issuances related to those filings may be expected in the thirdnext period.

The method continues with step 1422 where the growth and expenseco-processor identifies upcoming actions that occur in a fourth nextperiod. The upcoming actions in a fourth next period are identifiedbased on the existing portfolio matters and a likely outcome of actionsthat occurred in the current, first next, second next, and third nextperiods. With subsequent filings filed in the first next period and thethird next period, various stages of office actions and/or issuancespertaining to those filings may be expected. Further subsequent filingmay also be expected.

The method continues with step 1424 where the growth and expenseco-processor identifies upcoming actions that occur in a fifth nextperiod. The upcoming actions in a fifth next period are identified basedon the existing portfolio matters and a likely outcome of actions thatoccurred in the current, first next, second next, third next, and fourthnext periods. With subsequent filings filed in the first next period,third next, and fourth next periods, various stages of office actionsand/or issuances pertaining to those filings may be expected. Furthersubsequent filing may also be expected. Also, maintenance fees offissued patents may be expected.

The method continues with step 1426 where the growth and expenseco-processor identifies upcoming actions that occur in a n^(th) nextperiod. The n^(th) next period is set at a time in the future that makessense for the business and/or the technology. For example, the businessmay want to secure funding for developing a patent portfolio over aten-year period and needs an estimate of how much that will cost. Inanother example, the upcoming actions may be estimated up to only athird next period or less.

The upcoming actions in the n^(th) next period are identified based onthe existing portfolio matters and a likely outcome of actions thatoccurred in the proceeding periods. With subsequent filings filedthroughout, various stages of office actions and/or issuances pertainingto those filings may be expected. Further subsequent filing may also beexpected. Also, maintenance fees off issued patents may be expected.

FIG. 176 is a logic diagram of an example of a method for forecastingupcoming actions regarding patent protecting an MTU (market-tech unit)based on patent protected inventions of the current period by a growthand expense co-processor of an improved computer for technology. Themethod begins with step 1430 where the growth and expense co-processordetermines desired portfolio matters for a current period. Desiredportfolio matters pertain to amount of desired portfolio growth over thecurrent period and include new provisional and/or non-provisionalapplications, new subsequent filings (based off the new non-provisionalapplications), new PCT applications, etc. For example, the desiredportfolio matters for the current period may include filing five newnon-provisional applications.

The method continues with step 1432 where growth and expenseco-processor determines upcoming actions based on the desired currentperiod (CP) portfolio matters. For example, when the desired currentperiod portfolio matters include filing five new non-provisionalapplications, the upcoming actions include those filings, responses tooffice actions, and issuances. Desired upcoming subsequent filings(e.g., continuations, LPCs, continuations-in-part, etc.) based off thenon-provisional applications can also be estimated. Once patents issue,upcoming actions further includes paying maintenance fees.

The method continues with step 1434 where the growth and expenseco-processor identifies upcoming actions based on the desired portfoliomatters in the current period. A period may be set as any length of timethat makes sense for a business and/or a technology. For example, theperiod may be a year taking into account most businesses budget and planfor the current year. Other time periods such as a quarter or two yearsare also possible. Where the desired portfolio matters for the currentperiod include may include filing five new non-provisional applications,the upcoming actions that occur in the current period may include thosefilings and potentially one or more first office action responses and/orfirst office action allowances.

The method continues with step 1436 where the growth and expenseco-processor identifies upcoming actions that occur in a first nextperiod. The upcoming actions in a first next period are identified basedon the desired current period portfolio matters and a likely outcome ofactions that occurred in the current period. In an example of filingfive new non-provisional applications and one or more first officeaction responses (based off the five new non-provisional applications)in a current period, in the first next period one or more second officeaction responses (and associated requests for continued examination) maybe expected. Further, a certain number of subsequent filings off of thenon-provisional applications can be estimated for the first next period.

The method continues with step 1438 where the growth and expenseco-processor identifies upcoming actions that occur in a second nextperiod. The upcoming actions in a second next period are identifiedbased on the desired portfolio matters for the current period and alikely outcome of actions that occurred in the current and first nextperiod. In an example of filing five new non-provisional applicationsone or more first office actions response in a current period and one ormore second office actions in the first next period, in the second nextperiod one or more first office action responses after request forcontinued examination may be expected. Further, with subsequent filingsthat were filed in the first next period, an amount of office actionresponses related to those filings may be expected in the second nextperiod.

The method continues with step 1440 where the growth and expenseco-processor identifies upcoming actions that occur in a third nextperiod. The upcoming actions in a third next period are identified basedon the desired portfolio matters for the current period and a likelyoutcome of actions that occurred in the current, first next, and secondnext periods. In an example of filing five new non-provisionalapplications and one or more first office action responses in a currentperiod, filing one or more second office action responses in the firstnext period, and filing one or more first office action responses afterrequest for continued examination in the second next period, in thethird next period one or more issuances may be expected. With theissuances, subsequent filings such as a continuations may also beexpected. Further, with subsequent filings that were filed in the firstnext period and office action responses related to those filingsexpected in the second next period, additional office action responsesand/or issuances related to those filings may be expected in the thirdnext period.

The method continues with step 1442 where the growth and expenseco-processor identifies upcoming actions that occur in a fourth nextperiod. The upcoming actions in a fourth next period are identifiedbased on the desired portfolio matters for the current period and alikely outcome of actions that occurred in the current, first next,second next, and third next periods. With subsequent filings filed inthe first next period and the third next period, various stages ofoffice actions and/or issuances pertaining to those filings may beexpected. Further subsequent filing may also be expected.

The method continues with step 1444 where the growth and expenseco-processor identifies upcoming actions that occur in a fifth nextperiod. The upcoming actions in a fifth next period are identified basedon the desired portfolio matters for the current period and a likelyoutcome of actions that occurred in the current, first next, secondnext, third next, and fourth next periods. With subsequent filings filedin the first next period, third next, and fourth next periods, variousstages of office actions and/or issuances pertaining to those filingsmay be expected. Further subsequent filing may also be expected. Also,maintenance fees off issued patents may be expected.

The method continues with step 1446 where the growth and expenseco-processor identifies upcoming actions that occur in a n^(th) nextperiod. The n^(th) next period is set at a time in the future that makessense for the business and/or the technology. For example, the businessmay want to secure funding for developing a patent portfolio over aten-year period and needs an estimate of how much that will cost. Inanother example, the upcoming actions may be estimated up to only athird next period or less.

The upcoming actions in the nth next period are identified based on thedesired portfolio matters for the current period and a likely outcome ofactions that occurred in the proceeding periods. With subsequent filingsfiled throughout, various stages of office actions and/or issuancespertaining to those filings may be expected. Further subsequent filingmay also be expected. Also, maintenance fees off issued patents may beexpected.

FIG. 177 is a logic diagram of an example of a method for forecastingupcoming actions regarding patent protecting an MTU (market-tech unit)based on patent protected inventions of the first next period by agrowth and expense co-processor of an improved computer for technology.The method begins with step 1440 where the growth and expenseco-processor determines desired portfolio matters for a first nextperiod. Desired portfolio matters pertain to amount of desired portfoliogrowth over a first next period and include new provisional and/ornon-provisional applications, new subsequent filings (based off the newnon-provisional applications), new PCT applications, etc. For example,the desired portfolio matters for the first next period may includefiling five new non-provisional applications.

The method continues with step 1442 where the growth and expenseco-processor determines upcoming actions based on the desired first nextperiod (1NP) portfolio matters. For example, when the desired first nextperiod portfolio matters include filing five new non-provisionalapplications, the upcoming actions include those filings, responses tooffice actions, and issuances. Desired upcoming subsequent filings(e.g., continuations, LPCs, continuations-in-part, etc.) based off thenon-provisional applications can also be estimated. Once patents issue,upcoming actions further includes paying maintenance fees.

The method continues with step 1444 where the growth and expenseco-processor identifies upcoming actions based on the desired portfoliomatters in the first next period. Where the desired portfolio mattersfor the first next period include filing five new non-provisionalapplications, the upcoming actions that occur in the first next periodmay include those filings and potentially one or more first officeaction responses and/or first office action allowances.

The method continues with step 1446 where the growth and expenseco-processor identifies upcoming actions that occur in a second nextperiod. The upcoming actions in a second next period are identifiedbased on the desired first next period portfolio matters and a likelyoutcome of actions that occurred in the first next period. In an exampleof filing five new non-provisional applications and one or more firstoffice action responses (based off the five new non-provisionalapplications) in a first next period, in the second next period one ormore second office action responses (and associated requests forcontinued examination) may be expected. Further, a certain number ofsubsequent filings off of the non-provisional applications can beestimated for the second next period.

The method continues with step 1448 where the growth and expenseco-processor identifies upcoming actions that occur in a third nextperiod are identified. The upcoming actions in a third next period areidentified based on the desired portfolio matters for the first nextperiod and a likely outcome of actions that occurred in the first nextand second next period. In an example of filing five new non-provisionalapplications one or more first office actions response in a first nextperiod and one or more second office actions in the second next period,in the third next period one or more first office action responses afterrequest for continued examination may be expected. Further, withsubsequent filings that were filed in the second next period, an amountof office action responses related to those filings may be expected inthe third next period.

The method continues with step 1450 where the growth and expenseco-processor identifies upcoming actions that occur in a fourth nextperiod. The upcoming actions in a fourth next period are identifiedbased on the desired portfolio matters for the first next period and alikely outcome of actions that occurred in the first next, second next,and third next periods. In an example of filing five new non-provisionalapplications and one or more first office action responses in a firstnext period, filing one or more second office action responses in thesecond next period, and filing one or more first office action responsesafter request for continued examination in the third next period, in thefourth next period one or more issuances may be expected. With theissuances, subsequent filings such as a continuations may also beexpected. Further, with subsequent filings that were filed in the secondnext period and office action responses related to those filingsexpected in the third next period, additional office action responsesand/or issuances related to those filings may be expected in the fourthnext period.

The method continues with step 1452 where the growth and expenseco-processor identifies upcoming actions that occur in a fifth nextperiod. The upcoming actions in a fifth next period are identified basedon the desired portfolio matters for the first next period and a likelyoutcome of actions that occurred in the first next, second next, thirdnext, and fourth next periods. With subsequent filings filed in thesecond next period and the fourth next period, various stages of officeactions and/or issuances pertaining to those filings may be expected.Further subsequent filing may also be expected.

The method continues with step 1454 where the growth and expenseco-processor identifies upcoming actions that occur in a nth nextperiod. The nth next period is set at a time in the future that makessense for the business and/or the technology. For example, the businessmay want to secure funding for developing a patent portfolio over aten-year period and needs an estimate of how much that will cost. Inanother example, the upcoming actions may be estimated up to only athird next period or less.

The upcoming actions in the nth next period are identified based on thedesired portfolio matters for the first next period and a likely outcomeof actions that occurred in the proceeding periods. With subsequentfilings filed throughout, various stages of office actions and/orissuances pertaining to those filings may be expected. Furthersubsequent filing may also be expected. Also, maintenance fees offissued patents may be expected.

FIG. 178 is a logic diagram of an example of a method for forecastingupcoming actions regarding patent protecting an MTU (market-tech unit)based on patent protected inventions of the second next period by agrowth and expense co-processor of an improved computer for technology.The method begins with step 1460 where the growth and expenseco-processor determines desired portfolio matters for a second nextperiod. Desired portfolio matters pertain to amount of desired portfoliogrowth over a second next period and include new provisional and/ornon-provisional applications, new subsequent filings (based off the newnon-provisional applications), new PCT applications, etc. For example,the desired portfolio matters for the second next period may includefiling five new non-provisional applications.

The method continues with step 1462 where growth and expenseco-processor determines upcoming actions based on the desired secondnext period (2NP) portfolio matters. For example, when the desiredsecond next period portfolio matters include filing five newnon-provisional applications, the upcoming actions include thosefilings, responses to office actions, and issuances. Desired upcomingsubsequent filings (e.g., continuations, LPCs, continuations-in-part,etc.) based off the non-provisional applications can also be estimated.Once patents issue, upcoming actions further includes paying maintenancefees.

The method continues with step 1464 where the growth and expenseco-processor identifies upcoming actions based on the desired portfoliomatters in the second next period. Where the desired portfolio mattersfor the second next period include filing five new non-provisionalapplications, the upcoming actions that occur in the second next periodmay include those filings and potentially one or more first officeaction responses and/or first office action allowances.

The method continues with step 1468 where the growth and expenseco-processor identifies upcoming actions that occur in a third nextperiod. The upcoming actions in a third next period are identified basedon the desired second next period portfolio matters and a likely outcomeof actions that occurred in the second next period. In an example offiling five new non-provisional applications and one or more firstoffice action responses (based off the five new non-provisionalapplications) in a second next period, in the third next period one ormore second office action responses (and associated requests forcontinued examination) may be expected. Further, a certain number ofsubsequent filings off of the non-provisional applications can beestimated for the third next period.

The method continues with step 1470 where the growth and expenseco-processor identifies upcoming actions that occur in a fourth nextperiod. The upcoming actions in a fourth next period are identifiedbased on the desired portfolio matters for the second next period and alikely outcome of actions that occurred in the second next and thirdnext period. In an example of filing five new non-provisionalapplications one or more first office actions response in a second nextperiod and one or more second office actions in the third next period,in the fourth next period one or more first office action responsesafter request for continued examination may be expected. Further, withsubsequent filings that were filed in the third next period, an amountof office action responses related to those filings may be expected inthe fourth next period.

The method continues with step 1472 where the growth and expenseco-processor identifies upcoming actions that occur in a fifth nextperiod. The upcoming actions in a fifth next period are identified basedon the desired portfolio matters for the second next period and a likelyoutcome of actions that occurred in the second next, third next, andfourth next periods. In an example of filing five new non-provisionalapplications and one or more first office action responses in a secondnext period, filing one or more second office action responses in thethird next period, and filing one or more first office action responsesafter request for continued examination in the fourth next period, inthe fifth next period one or more issuances may be expected. With theissuances, subsequent filings such as a continuations may also beexpected. Further, with subsequent filings that were filed in the thirdnext period and office action responses related to those filingsexpected in the fourth next period, additional office action responsesand/or issuances related to those filings may be expected in the fifthnext period.

The method continues with step 1474 where the growth and expenseco-processor identifies upcoming actions that occur in a nth nextperiod. The nth next period is set at a time in the future that makessense for the business and/or the technology. For example, the businessmay want to secure funding for developing a patent portfolio over aten-year period and needs an estimate of how much that will cost. Inanother example, the upcoming actions may be estimated up to only athird next period or less.

The upcoming actions in the nth next period are identified based on thedesired portfolio matters for the second next period and a likelyoutcome of actions that occurred in the proceeding periods. Withsubsequent filings filed throughout, various stages of office actionsand/or issuances pertaining to those filings may be expected. Furthersubsequent filing may also be expected. Also, maintenance fees offissued patents may be expected.

FIG. 179 is a logic diagram of an example of a method for forecastingupcoming actions regarding patent protecting an MTU (market-tech unit)based on patent protected inventions of the third next period by agrowth and expense co-processor of an improved computer for technology.The method begins with step 1480 where the growth and expenseco-processor determines desired portfolio matters for a third nextperiod. Desired portfolio matters pertain to amount of desired portfoliogrowth over a third next period and include new provisional and/ornon-provisional applications, new subsequent filings (based off the newnon-provisional applications), new PCT applications, etc. For example,the desired portfolio matters for the third next period may includefiling ten new non-provisional applications.

The method continues with step 1482 where the growth and expenseco-processor determines upcoming actions based on the desired third nextperiod (3NP) portfolio matters. For example, when the desired third nextperiod portfolio matters include filing ten new non-provisionalapplications, the upcoming actions include those filings, responses tooffice actions, and issuances. Desired upcoming subsequent filings(e.g., continuations, LPCs, continuations-in-part, etc.) based off thenon-provisional applications can also be estimated. Once patents issue,upcoming actions further includes paying maintenance fees.

The method continues with step 1484 where the growth and expenseco-processor identifies upcoming actions based on the desired portfoliomatters in the third next period. Where the desired portfolio mattersfor the third next period include filing ten new non-provisionalapplications, the upcoming actions that occur in the third next periodmay include those filings and one or more first office action responsesand/or first office action allowances.

The method continues with step 1486 where the growth and expenseco-processor identifies upcoming actions that occur in a fourth nextperiod. The upcoming actions in a fourth next period are identifiedbased on the desired third next period portfolio matters and a likelyoutcome of actions that occurred in the third next period. In an exampleof filing ten new non-provisional applications and one or more firstoffice action responses (based off the ten new non-provisionalapplications) in a third next period, in the fourth next period one ormore second office action responses (and associated requests forcontinued examination) may be expected. Further, a certain number ofsubsequent filings off of the non-provisional applications can beestimated for the fourth next period.

The method continues with step 1488 where the growth and expenseco-processor identifies upcoming actions that occur in a fifth nextperiod. The upcoming actions in a fifth next period are identified basedon the desired portfolio matters for the third next period and a likelyoutcome of actions that occurred in the third next and fourth nextperiod. In an example of filing ten new non-provisional applications oneor more first office actions response in a third next period and one ormore second office actions in the fourth next period, in the fifth nextperiod one or more first office action responses after request forcontinued examination may be expected. Further, with subsequent filingsthat were filed in the fourth next period, an amount of office actionresponses related to those filings may be expected in the fifth nextperiod.

The method continues with step 1489 where the growth and expenseco-processor identifies upcoming actions that occur in a nth nextperiod. The nth next period is set at a time in the future that makessense for the business and/or the technology. For example, the businessmay want to secure funding for developing a patent portfolio over aten-year period and needs an estimate of how much that will cost. Inanother example, the upcoming actions may be estimated up to only afifth next period or less.

The upcoming actions in the nth next period are identified based on thedesired portfolio matters for the third next period and a likely outcomeof actions that occurred in the proceeding periods. With subsequentfilings filed throughout, various stages of office actions and/orissuances pertaining to those filings may be expected. Furthersubsequent filing may also be expected. Also, maintenance fees offissued patents may be expected.

FIG. 180 is a logic diagram of an example of a method for forecastingupcoming actions regarding patent protecting an MTU (market-tech unit)based on patent protected inventions of the fourth next period by agrowth and expense co-processor of an improved computer for technology.The method begins with step 1490 where the growth and expenseco-processor determines desired portfolio matters for a fourth nextperiod are determined. Desired portfolio matters pertain to amount ofdesired portfolio growth over a fourth next period and include newprovisional and/or non-provisional applications, new subsequent filings(based off the new non-provisional applications), new PCT applications,etc. For example, the desired portfolio matters for the fourth nextperiod may include filing ten new non-provisional applications.

The method continues with step 1492 where the growth and expenseco-processor determines upcoming actions based on the desired fourthnext period (4NP) portfolio matters. For example, when the desiredfourth next period portfolio matters include filing ten newnon-provisional applications, the upcoming actions include thosefilings, responses to office actions, and issuances. Desired upcomingsubsequent filings (e.g., continuations, LPCs, continuations-in-part,etc.) based off the non-provisional applications can also be estimated.Once patents issue, upcoming actions further includes paying maintenancefees.

The method continues with step 1494 where the growth and expenseco-processor identifies upcoming actions based on the desired portfoliomatters in the fourth next period. Where the desired portfolio mattersfor the fourth next period include filing ten new non-provisionalapplications, the upcoming actions that occur in the fourth next periodmay include those filings and one or more first office action responsesand/or first office action allowances.

The method continues with step 1496 where the growth and expenseco-processor identifies upcoming actions that occur in a fifth nextperiod. The upcoming actions in a fifth next period are identified basedon the desired fourth next period portfolio matters and a likely outcomeof actions that occurred in the fourth next period. In an example offiling ten new non-provisional applications and one or more first officeaction responses (based off the ten new non-provisional applications) ina fourth next period, in the fifth next period one or more second officeaction responses (and associated requests for continued examination) maybe expected. Further, a certain number of subsequent filings off of thenon-provisional applications can be estimated for the fifth next period.

The method continues with step 1498 where the growth and expenseco-processor identifies upcoming actions that occur in a nth nextperiod. The nth next period is set at a time in the future that makessense for the business and/or the technology. For example, the businessmay want to secure funding for developing a patent portfolio over aten-year period and needs an estimate of how much that will cost. Inanother example, the upcoming actions may be estimated up to only afifth next period or less.

The upcoming actions in the nth next period are identified based on thedesired portfolio matters for the fourth next period and a likelyoutcome of actions that occurred in the proceeding periods. Withsubsequent filings filed throughout, various stages of office actionsand/or issuances pertaining to those filings may be expected. Furthersubsequent filing may also be expected. Also, maintenance fees offissued patents may be expected.

FIG. 181 is a logic diagram of an example of a method for forecastingupcoming actions regarding patent protecting an MTU (market-tech unit)based on patent protected inventions of the fifth next period by agrowth and expense co-processor of an improved computer for technology.The method begins with step 1500 where the growth and expenseco-processor determines desired portfolio matters for a fifth nextperiod. Desired portfolio matters pertain to an amount of desiredportfolio growth over a fifth next period and include new provisionaland/or non-provisional applications, new subsequent filings (based offthe new non-provisional applications), new PCT applications, etc. Forexample, the desired portfolio matters for the fifth next period mayinclude filing three new non-provisional applications.

The method continues with step 1502 where the growth and expenseco-processor determines upcoming actions based on the desired fifth nextperiod (5NP) portfolio matters. For example, when the desired fifth nextperiod portfolio matters include filing three new non-provisionalapplications, the upcoming actions include those filings, responses tooffice actions, and issuances. Desired upcoming subsequent filings(e.g., continuations, LPCs, continuations-in-part, etc.) based off thenon-provisional applications can also be estimated. Once patents issue,upcoming actions further includes paying maintenance fees.

The method continues with step 1504 where the growth and expenseco-processor identifies upcoming actions based on the desired portfoliomatters in the fifth next period. Where the desired portfolio mattersfor the fifth next period include filing three new non-provisionalapplications, the upcoming actions that occur in the fifth next periodmay include those filings and one or more first office action responsesand/or first office action allowances.

The method continues with step 1506 where the growth and expenseco-processor identifies upcoming actions that occur in a nth nextperiod. The nth next period is set at a time in the future that makessense for the business and/or the technology. For example, the businessmay want to secure funding for developing a patent portfolio over aten-year period and needs an estimate of how much that will cost.

The upcoming actions in the nth next period are identified based on thedesired portfolio matters for the fifth next period and a likely outcomeof actions that occurred in the proceeding periods. With subsequentfilings filed throughout, various stages of office actions and/orissuances pertaining to those filings may be expected. Furthersubsequent filing may also be expected. Also, maintenance fees offissued patents may be expected.

FIG. 182 is a logic diagram of an example of a method for forecastingupcoming actions regarding patent protecting an MTU (market-tech unit)based on patent protected inventions of the nth next period by a growthand expense co-processor of an improved computer for technology. Themethod begins with step 1510 where the growth and expense co-processordetermines desired portfolio matters for an nth next period. Desiredportfolio matters pertain to an amount of desired portfolio growth overan nth next period and include new provisional and/or non-provisionalapplications, new subsequent filings (based off the new non-provisionalapplications), new PCT applications, etc. For example, the desiredportfolio matters for the nth next period may include filing five newnon-provisional applications.

The method continues with step 1512 where the growth and expenseco-processor determines upcoming actions based on the desired nth nextperiod (“n″NP) portfolio matters. For example, when the desired nth nextperiod portfolio matters include filing five new non-provisionalapplications, the upcoming actions include those filings, responses tooffice actions, and issuances. Desired upcoming subsequent filings(e.g., continuations, LPCs, continuations-in-part, etc.) based off thenon-provisional applications can also be estimated. Once patents issue,upcoming actions further includes paying maintenance fees.

The method continues with step 1514 where the growth and expenseco-processor identifies upcoming actions that occur in the nth nextperiod. Where the desired portfolio matters for the nth next periodinclude filing five new non-provisional applications, the upcomingactions that occur in the nth next period may include those filings andone or more first office action responses and/or first office actionallowances.

FIG. 183 is a logic diagram of an example of a method for combiningactions regarding patent protecting an MTU (market-tech unit) that areforecasted to occur in the current period by a growth and expenseco-processor of an improved computer for technology. For a currentperiod forecast, the upcoming actions that occur in the current periodfrom the existing portfolio matters (as discussed with reference to step1414 of FIG. 175 ) are combined with the upcoming actions that occur inthe current in the current period from the desired portfolio matters ofthe current period (as discussed with reference to step 1434 of FIG. 176).

FIG. 184 is a logic diagram of an example of a method for combiningactions regarding patent protecting an MTU (market-tech unit) that areforecasted to occur in the first next period by a growth and expenseco-processor of an improved computer for technology. For a first nextperiod forecast, the upcoming actions that occur in the first nextperiod from the existing portfolio matters (as discussed with referenceto step 1416 of FIG. 175 ) are combined with the upcoming actions thatoccur in the first next period from desired portfolio matters of acurrent period (as discussed with reference to step 1436 of FIG. 176 )and the upcoming actions that occur in the first next period fromdesired portfolio matters of the first next period (as discussed withreference to step 1444 of FIG. 177 ).

FIG. 185 is a logic diagram of an example of a method for combiningactions regarding patent protecting an MTU (market-tech unit) that areforecasted to occur in the second next period by a growth and expenseco-processor of an improved computer for technology. For a second nextperiod forecast, the upcoming actions that occur in the second nextperiod from the existing portfolio matters (as discussed with referenceto step 1418 of FIG. 175 ) are combined with the upcoming actions thatoccur in the second next period from desired portfolio matters of acurrent period (as discussed with reference to step 1438 of FIG. 176 ),the upcoming actions that occur in the second next period from desiredportfolio matters of the first next period (as discussed with referenceto step 1446 of FIG. 177 ), and the upcoming actions that occur in thesecond next period from desired portfolio matters of the second nextperiod (as discussed with reference to step 1464 of FIG. 178 ).

FIG. 186 is a logic diagram of an example of a method for combiningactions regarding patent protecting an MTU (market-tech unit) that areforecasted to occur in the third next period by a growth and expenseco-processor of an improved computer for technology. For a third nextperiod forecast, the upcoming actions that occur in the third nextperiod from the existing portfolio matters (as discussed with referenceto step 1420 of FIG. 175 ) are combined with the upcoming actions thatoccur in the third next period from desired portfolio matters of acurrent period (as discussed with reference to step 1440 of FIG. 176 ),the upcoming actions that occur in the third next period from desiredportfolio matters of the first next period (as discussed with referenceto step 1448 of FIG. 177 ), the upcoming actions that occur in the thirdnext period from desired portfolio matters of the second next period (asdiscussed with reference to step 1468 of FIG. 178 ), and the upcomingactions that occur in the third next period from desired portfoliomatters of the third next period (as discussed with reference to step1484 of FIG. 179 ).

FIG. 187 is a logic diagram of an example of a method for combiningactions regarding patent protecting an MTU (market-tech unit) that areforecasted to occur in the fourth next period by a growth and expenseco-processor of an improved computer for technology. For a fourth nextperiod forecast, the upcoming actions that occur in the fourth nextperiod from the existing portfolio matters (as discussed with referenceto step 1422 of FIG. 175 ) are combined with the upcoming actions thatoccur in the fourth next period from desired portfolio matters of acurrent period (as discussed with reference to step 1442 of FIG. 176 ),the upcoming actions that occur in the fourth next period from desiredportfolio matters of the first next period (as discussed with referenceto step 1450 of FIG. 177 ), the upcoming actions that occur in thefourth next period from desired portfolio matters of the second nextperiod (as discussed with reference to step 1470 of FIG. 178 ), theupcoming actions that occur in the fourth next period from desiredportfolio matters of the third next period (as discussed with referenceto step 1486 of FIG. 179 ), and the upcoming actions that occur in thefourth next period from desired portfolio matters of the fourth nextperiod (as discussed with reference to step 1494 of FIG. 180 ).

FIG. 188 is a logic diagram of an example of a method for combiningactions regarding patent protecting an MTU (market-tech unit) that areforecasted to occur in the fifth next period by a growth and expenseco-processor of an improved computer for technology. For a fifth nextperiod forecast, the upcoming actions that occur in the fifth nextperiod from the existing portfolio matters (as discussed with referenceto step 1424 of FIG. 175 ) are combined with the upcoming actions thatoccur in the fifth next period from desired portfolio matters of acurrent period (as discussed with reference to step 1444 of FIG. 176 ),the upcoming actions that occur in the fifth next period from desiredportfolio matters of the first next period (as discussed with referenceto step 1452 of FIG. 177 ), the upcoming actions that occur in the fifthnext period from desired portfolio matters of the second next period (asdiscussed with reference to step 1472 of FIG. 178 ), the upcomingactions that occur in the fifth next period from desired portfoliomatters of the third next period (as discussed with reference to step1488 of FIG. 179 ), the upcoming actions that occur in the fifth nextperiod from desired portfolio matters of the fourth next period (asdiscussed with reference to step 1496 of FIG. 180 ), and the upcomingactions that occur in the fifth next period from desired portfoliomatters of the fifth next period (as discussed with reference to step1504 of FIG. 181 ).

FIG. 189 is a logic diagram of an example of a method for combiningactions regarding patent protecting an MTU (market-tech unit) that areforecasted to occur in the sixth next period by a growth and expenseco-processor of an improved computer for technology. For a sixth nextperiod forecast, the upcoming actions that occur in the sixth nextperiod from the existing portfolio matters are combined with theupcoming actions that occur in the sixth next period from desiredportfolio matters of a current period, the upcoming actions that occurin the sixth next period from desired portfolio matters of the firstnext period, the upcoming actions that occur in the sixth next periodfrom desired portfolio matters of the second next period, the upcomingactions that occur in the sixth next period from desired portfoliomatters of the third next period, the upcoming actions that occur in thesixth next period from desired portfolio matters of the fourth nextperiod, the upcoming actions that occur in the sixth next period fromdesired portfolio matters of the fifth next period, and the upcomingactions that occur in the sixth next period from desired portfoliomatters of the sixth next period.

FIG. 190 is a logic diagram of an example of a method for combining USand international actions regarding patent protecting multiple MTUs(market-tech units) that are forecasted to occur in the current periodby a growth and expense co-processor of an improved computer fortechnology. For each market-tech unit #1-#x of a technology, a currentperiod forecast can be generated as discussed with reference to FIGS.176 and 183. Further, a current period forecast of each market-tech unit#1-#x of a technology can be generated with respect to a particularcountry (e.g., the U.S., foreign countries E-Q, etc.). The currentperiod forecast can be shown for each of these categories or combinedinto an overall current period forecast.

FIG. 191 is a logic diagram of an example of a method for combining USand international actions regarding patent protecting multiple MTUs(market-tech units) that are forecasted to occur in the first nextperiod by a growth and expense co-processor of an improved computer fortechnology. For each market-tech unit #1-#x of a technology, a firstnext period forecast can be generated as discussed with reference toFIGS. 177 and 184. Further, a first next period forecast of eachmarket-tech unit #1-#x of a technology can be generated with respect toa particular country (e.g., the U.S., foreign countries E-Q, etc.). Thefirst next period forecast can be shown for each of these categories orcombined into an overall first next period forecast.

FIG. 192 is a logic diagram of an example of a method for combining USand international actions regarding patent protecting multiple MTUs(market-tech units) that are forecasted to occur in the second nextperiod by a growth and expense co-processor of an improved computer fortechnology. For each market-tech unit #1-#x of a technology, a secondnext period forecast can be generated as discussed with reference toFIGS. 178 and 185. Further, a second next period forecast of eachmarket-tech unit #1-#x of a technology can be generated with respect toa particular country (e.g., the U.S., foreign countries E-Q, etc.). Thesecond next period forecast can be shown for each of these categories orcombined into an overall second next period forecast.

FIG. 193 is a logic diagram of an example of a method for combining USand international actions regarding patent protecting multiple MTUs(market-tech units) that are forecasted to occur in the third nextperiod by a growth and expense co-processor of an improved computer fortechnology. For each market-tech unit #1-#x of a technology, a thirdnext period forecast can be generated as discussed with reference toFIGS. 179 and 186. Further, a third next period forecast of eachmarket-tech unit #1-#x of a technology can be generated with respect toa particular country (e.g., the U.S., foreign countries E-Q, etc.). Thethird next period forecast can be shown for each of these categories orcombined into an overall third next period forecast.

FIG. 194 is a logic diagram of an example of a method for combining USand international actions regarding patent protecting multiple MTUs(market-tech units) that are forecasted to occur in the fourth nextperiod by a growth and expense co-processor of an improved computer fortechnology. For each market-tech unit #1-#x of a technology, a fourthnext period forecast can be generated as discussed with reference toFIGS. 180 and 187. Further, a fourth next period forecast of eachmarket-tech unit #1-#x of a technology can be generated with respect toa particular country (e.g., the U.S., foreign countries E-Q, etc.). Thefourth next period forecast can be shown for each of these categories orcombined into an overall fourth next period forecast.

FIG. 195 is a logic diagram of an example of a method for combining USand international actions regarding patent protecting multiple MTUs(market-tech units) that are forecasted to occur in the 5^(th) nextperiod by a growth and expense co-processor of an improved computer fortechnology. For each market-tech unit #1-#x of a technology, a fifthnext period forecast can be generated as discussed with reference toFIGS. 181 and 188. Further, a fifth next period forecast of eachmarket-tech unit #1-#x of a technology can be generated with respect toa particular country (e.g., the U.S., foreign countries E-Q, etc.). Thefifth next period forecast can be shown for each of these categories orcombined into an overall fifth next period forecast.

FIG. 196 is a logic diagram of an example of a method for combining USand international actions regarding patent protecting multiple MTUs(market-tech units) that are forecasted to occur in the 6^(th) nextperiod by a growth and expense co-processor of an improved computer fortechnology. For each market-tech unit #1-#x of a technology, a sixthnext period forecast can be generated as discussed with reference toFIG. 189 . Further, a sixth next period forecast of each market-techunit #1-#x of a technology can be generated with respect to a particularcountry (e.g., the U.S., foreign countries E-Q, etc.). The sixth nextperiod forecast can be shown for each of these categories or combinedinto an overall sixth next period forecast.

FIG. 197 is a logic diagram of an example of a method for forecastingnew inventions per period to patent protect for an MTU (market-tech unitor m-t unit) by a growth and expense co-processor of an improvedcomputer for technology. The method begins with step 1520 where thegrowth and expense co-processor identifies one or more comparableexisting market-tech units. For example, the MSBTP (marketing, sales,business, technical, and patent) data gathering section of the improvedcomputer for technology executes machine learning and/or artificialintelligence programs to routinely (e.g., periodically, pseudo randomly,upon request, etc.) ingests a large number of documents and dissect eachdocument for relevant information regarding existing MTUs. The growthand expense co-processor compares (e.g., by classification data,keywords, etc.) a new or incoming MTU to existing MTUs to identifycomparable existing MTUs. For example, if the MTU is improved circuitryfor use in touchscreens, the one or more comparable existing MTUs mayinclude touchscreen devices.

The method continues with step 1522 where the growth and expenseco-processor determines invention life cycle(s) for the comparableexisting MTUs (e.g., based on gathered data from at least the MSBTP datagathering section). For example, an invention life cycle for acomparable existing MTU includes generations (previous, current, and/ornext) and the phases of each generation. A generational life of a MTUincludes a create phase, a deploy phase, an optimize phase, a maturephase, and a decline phase. In the create phase, the MTU is beingcreated and not yet commercialized. In the deploy phase, an initialcommercial embodiment of the MTU is made publicly available. In theoptimize phase, commercial embodiments of the MTU are optimized forperformance, production costs, features, and/or other optimizations andrevenue from the commercial embodiments increases. In the mature phase,the commercial embodiments of the MTU are optimized and revenue from thecommercial embodiments increases at a decreasing rate. In the declinephase, revenue from the commercial embodiments of the MTU decreases atan increasing rate.

The method continues with step 1524 where growth and expenseco-processor determines the completion of the invention life cycle. Forexample, each generation of the invention life cycle includes a lifespan and each phase of each generation includes a time frame. Thecompletion of the invention life cycle estimates when the invention lifecycle ends based on the expected life span of each generation and thetime frame of each phase. For example, a comparable MTU may be in aoptimize phase and the completion of the invention life cycle (e.g., theend of the decline phase) may be estimated at 5 years from today.

The method continues with step 1526 where the growth and expenseco-processor determines a total number of inventions per existingcomparable MTU based on the completion of the invention life cycle. Thecreation of inventions occurs over the life of the MTU. Fundamentalinventions are typically created during the create phase and a portionof the deploy phase. Commercially necessary inventions are typicallycreated in part of the create phase, throughout the deploy phase andinto the optimize phase. Commercial expansion inventions are typicallycreated in part of the deploy phase through the mature phase and intothe decline phase. The growth and expense co-processor is operable toanalyze inventions that currently exist (e.g., identify inventions fromissued patents and pending patent applications gathered via at least theMSBTP data gathering section) for a comparable existing MTU but alsoestimate a remaining amount of inventions that are likely to occur forthe remainder of its invention life cycle based on market statistics,historical data, etc. The existing and estimated remaining inventionsfor each existing comparable MTU are combined to determine the totalnumber of inventions per existing comparable MTU.

The method continues with step 1528 where the growth and expenseco-processor determines a complexity factor of the new market-tech unitwith respect to the comparable existing MTUs. The complexity factor maybe a value that ranges from 0.5 to 4.0 and indicates a change in thelevel of innovation to develop the new MTU technology with respect tothe level of innovation used to develop the comparable existing MTUtechnology. Determining the complexity factor may include comparing howsimilar the comparable existing MTUs are to the one or more new MTUs.For example, the new MTU may involve an innovative tweak to an alreadyexisting component in which case the complexity factor may be a 1.0 orless. In another example, the new MTU may involve a completely new,revolutionary component that will require development from the ground upin which case the complexity factor may be closer to a 4.0.

The method continues with step 1530 where the growth and expenseco-processor determines a total number of inventions for the new MTUbased on the complexity factor and the total number of inventions ofexisting MTUs. For example, if the number of inventions of comparableexisting MTUs is 15,000 and the complexity factor is 1.0, the totalnumber of inventions for the new MTU may be calculated as 15,000 (e.g.,1.0 ×15,000). In another example, when the new MTU is more complex thanexisting comparable MTUs, more inventions may be involved in thedevelopment and launch of the new MTU. For example, if the number ofinventions of comparable existing MTUs is 15,000 and the complexityfactor is 4.0, the total number of inventions for the new MTU may becalculated at 60,000 (e.g., 4.0 ×15,000).

The method continues with step 1532 where the growth and expenseco-processor determines completion of invention life cycle for the newMTU. Based on the current stage of the invention life cycle of the newMTU, the type of technology involved, comparison to similartechnologies, market data, historical data, etc., an estimatedcompletion of the invention life cycle for the new MTU can bedetermined. Each generation of the invention life cycle includes a lifespan and each phase of each generation includes a time frame. Thecompletion of the invention life cycle estimates when the invention lifecycle ends based on the expected life span of each generation and thetime frame of each phase. For example, the new MTU may be in a createphase and the completion of the invention life cycle (e.g., the end ofthe decline phase) may be estimated at 10 years from today.

The method continues with step 1534 where the growth and expenseco-processor determines the remaining number of inventions for new MTUbased on the completion of the invention life cycle. Based on thegeneration and phase the MTU is currently in and the completion of theinvention life cycle, a remaining number of inventions for the new MTUcan be determined. For example, if the MTU is currently in year two of aten year technology lifespan, estimated inventions for the remainingeight years can be determined from the total number of inventions forthe new MTU.

The method continues with step 1536 where the growth and expenseco-processor determines a number of inventions to protect for the newMTU based on a desired patent position. The desired patent position iswith respect to others regarding a patent dispute involving thetechnology and can range from weak to superior. A superior patentposition is one in which the patent holder has a superior patentposition with respect to all others involved with the technology. A weakpatent position is one in which the patent holder has an inferior patentposition with respect to most, if not all, others involved with thetechnology. The number of inventions to protect may be determined basedon a percentage of the total number of inventions estimated for thelifespan of the MTU. For example, a superior patent position be a higherpercentage and a weak patent position may be a lower percentage.

The method continues with step 1538 where the growth and expenseco-processor determines per period inventions to protect for the totalnumber of inventions to protect. For example, a period may be set at ayear and the invention lifespan is determined to be ten years where thecurrent year is year two. For year two, and the remaining eight years,the total number of inventions for each year (i.e., period) isdetermined. Depending on the phase (e.g., create, deploy, optimize,mature, and decline) of the MTU, more inventions may be allotted toparticular periods. For example, a peak amount of inventions may need tobe protected during the end of the optimize stage (e.g., see FIGS.199-200 ). If the optimize stage is determined to be years 4-8 of thetechnology life, years 4-8 may see an increase in the amount ofinventions protected of the total number of inventions.

The method continues with step 1540 where the growth and expenseco-processor determines whether to bundle inventions. For example, apatent application for a bundle of inventions includes “x” number ofinventions. One of the inventions is selected to be the claimedinvention. The remaining “x-1” inventions (i.e., Legal PlaceholderInventions) are disclosed in an enabling manner for subsequentconversion to a patent application.

The upfront cost of filing a patent application with a bundle ofinventions is significantly less than filing separate patentapplications for each of the inventions in the bundle. For example,assume that the attorney fee for preparing and filing a patentapplication is $14,000, the government filing fee for a patentapplication is $1,000, and the attorney fee for a detailed discussionfor a legal placeholder invention is $4,000 and further assume there are6 inventions in a bundle. The cost to file one patent application with abundle of 6 inventions is $35,000 ($14,000+$1,000 +514,000)). The costto file six separate patent applications is $90,000(6*($14,000+$1,000)).

When it is determined to pursue application bundles, the methodcontinues with step 1542 where the growth and expense co-processordetermines a number of inventions per bundle. The number of inventionsper bundle may be determined based on a typical number of inventionsrelating to a particular topic at a particular phase in the technology,a desired length of the specification and amount of drawings, desiredspend, and/or the amount of total inventions desired for bundling. Forexample, the number of inventions per bundle may be determined to be 4.

When the number of inventions per bundle are determined or it isdetermined not to bundle inventions, the method continues with step 1544where the growth and expense co-processor determines whether to fileapplications (e.g., bundles if coming from step 1542) provisionally.

Patent law provides that a patent application for an invention can befiled as a provisional patent application or it can be filed as anon-provisional utility patent application. If a provisional applicationis filed, it must be converted into a non-provisional utility patentapplication within 12 months of its filing date. The provisional patentapplication expires 12 months after its filing date.

In general, a provisional patent application has less requirements thana non-provisional utility patent application (e.g., no claims) and ischeaper to file (e.g., lower attorney fees and governmental filing fees)to establish a priority date for the disclosed subject matter regardingthe invention. Therefore, depending upon the time frame for filing andthe funds available, provisional applications may initially be chosenover non-provisional applications in certain cases.

A provisional patent application is not examined or reviewed by thePatent Office. As such, the detailed discussion of the invention may bealmost any length and/or of any level of detail. If, however, thedetailed discussion of the provisional application is lacking anenabling disclosure, does not disclose the best mode of operation,and/or is lacking support for the claims, as are required for anon-provisional utility patent application, the added detaileddescription is not afforded the filing date of the provisional patentapplication. It is given the filing date of the non-provisional utilitypatent application. While patent law allows for the filing ofprovisional patent applications, it is typically recommended to file anon-provisional patent application when time allows. This ensures thatall of the requirements of the detailed description are met, and theapplication is in queue for examination by the Patent Office.

When it is determined that one or more provisional applications are tobe filed, the method continues with step 1546 where the growth andexpense co-processor determines the number of provisional applications.The number of provisional applications may be based on the number oftotal inventions, the number of bundle applications, the level ofcompleteness of the invention, the time frame in which the applicationsshould or need to be filed, the current phase of the technology, adesired spend, etc.

When it is determined that one or more provisional applications are notto be filed or after the number of provisional applications aredetermined at step 1546, the method continues with step 1548 where thegrowth and expense co-processor determines the number of non-provisionalapplications. The number of non-provisional applications may be based onthe number of total inventions, the number of the bundle applications,the number of provisional applications filed, the level of completenessof the invention, the current phase of the technology, a desired spend,etc.

The method continues with step 1549 where the growth and expenseco-processor determines new application filing expenses per period. Whena desired number of new applications are determined per period, thefiling expenses can be calculated based on attorney fees and governmentfees associated for application filings. If the amount is too high, thedesired patent position can be adjusted to reduce the amount of newfilings and reduce expenses. Other options to reduce filing expenseswithout weakening a desired patent position may include filing moreprovisional applications over non-provisional applications initially,filing more bundles applications, and/or including more inventions perbundle.

FIG. 198 is a logic diagram of another example of a method forforecasting new inventions per period to patent protect for an MTU(market-tech unit) by a growth and expense co-processor of an improvedcomputer for technology. FIG. 198 is a new application forecastingmethod related to the technical challenge to inventive embodimentmapping discussed with reference to FIG. 65 . The forecasting methodaims to estimate a quantity of new application filings and, if possible,identify inventive subject matter. Forecasted data may be based oninformation pulled from engineers during invention harvesting sessions,advanced inventing sessions, and/or determined based on historical data(e.g., analyzing the inventive embodiment chain of comparable knowntechnical challenges).

The method begins with step 1550 where for an MTU, near-term, mid-term,and/or long-term technical (tech) challenges are forecasted. In general,a technical challenge corresponds to a technical aspect of a uniquevalue proposition (UVP) of quantified technology, a technical aspect ofa marketable feature of products embodying (or likely to embody) thequantified technology, and/or other technical aspect of the quantifiedtechnology. For example, for the UVP of a better user experience fortouch screens and its associated marketable features, the techchallenges include, but are not limited to, improve signal to noiseratio of touch sensing, improve video graphics processing, and improvetouch detection processing and image rendering thereof.

The method continues with step 1552 where for a technical challenge, theproblem(s) to be solved are forecasted. Each technical challengeprovides motivation for one or more problems. For example, the technicalchallenge of accurate battery sensing provides motivation for theproblems of “how to sense a battery with negligible effect on thebattery” and “how to use a plurality of AC signals to sense a battery.”As another example, the technical challenge of improved batterydischarge modeling provides motivation for the problem of “how to modelbattery discharging based on the more accurate sensed battery data.” Asa further example, the tech challenge of improved battery chargemodeling provides motivation for the problem of “how to model batterycharging based on the more accurate sensed battery data.”

The method continues with step 1554 where for a problem, inventiveconcept(s) for potentially solving the problem are forecasted. Aninventive concept is a conceptual way of solving a problem. As anexample, for the problem of “improving force transfer between the bodyand the ground via the shoes,” an inventive concept is to have differentforce transfer properties in the heel than in the forefoot of sole toimprove engagement of the foot to the shoe and the shoe to the ground.Another inventive concept for this problem is to have a series ofhorizontal force to vertical force focusing elements in the sole toimprove engagement of the foot to the shoe and the shoe to the ground.

The method continues with step 1556 where for an inventive concept,implementation elements, implementation mechanisms, and implementationvariants are forecasted. An implementation element is a tangiblephysical and/or virtual part of an inventive concept. An implementationmechanism is an aspect of an implementation element that can be changed.An implementation variant is a variation of an implementation elementand/or a variation of an implementation mechanism.

As an example, an inventive concept to a solve a problem is “to do X toA, Y to B, and Z to C”. In this example, A, B, and C are implementationelements and X, Y, and Z are implementation mechanisms. Implementationvariants would be A′ for A, B′ for B, C′ for C, x for X, y for Y, and/orz for Z.

The method continues with step 1558 where potential solution(s) fromimplementation elements, implementation mechanisms, and implementationvariants are forecasted. From the implementation elements, theimplementation mechanisms, and the implementation variants, the growthand expense co-processor identifies one or more solutions, where asolution is a specific combination of the implementation elements, theimplementation mechanisms, and the implementation variants. For example,one solution is “do X to A, Y to B, and Z to C”; a second solution is“do x to A, y to B, and z to C”, a third solution is “do X to A′, Y toB′, and Z to C”, and fourth solution is “do x to A′, y to B′, and z toC”.

The method continues with step 1560 where for a solution, a set ofnovelty nuggets is forecasted. A novelty nugget is a technical aspect tois believed to be novel in light of known prior art. Continuing with theexample of above, for the first solution of do X to A, Y to B, and Z toC″, the growth and expense co-processor may identify the novelty nuggetsof “do X to A”, “do Y to B”, and “do Z to C”.

The method continues with step 1562 where for a set of novelty nuggets,potential one or more inventive embodiments are forecasted. Depending onthe nature of the novelty nuggets, the growth and expense co-processoridentifies one or more inventive embodiments, where an inventiveembodiment represents a patentable invention. The growth and expenseco-processor identifies specific combinations of the novelty nuggets toproduce the inventive embodiments. For the example discussed above, thegrowth and expense co-processor determines that the combination of “do Xto A” and “do Z to C” is an invention embodiment and “do Y to B” is aseparate inventive embodiment.

The growth and expense co-processor then determines an invention typefor each of the inventive embodiments. Invention types includefundamental, commercially necessary, commercial expansion, newfundamental, commercial expansion regarding new uses of fundamentalinventions, commercial expansion of new fundamental inventions,commercial expansion regarding vertical integration, commercialexpansion regarding horizontal integration, commercial expansionregarding competitor speed bump, commercial expansion regardingpotential standard essential, and/or commercial expansion regardingpotential non-essential but commercially necessary standards related.

The method continues with step 1564 where it is determined whether moreforecasted solutions exist. As new data is ingested, new solutions mayarise. When more forecasted solutions are determined, the methodbranches back to step 1560 where a set of novel nuggets are forecastedbased on the new solutions.

When more forecasted solutions are not determined at step 1564, themethod continues with step 1566 where it is determined whether moreforecasted inventive concepts exist. As new data is ingested, newinventive concepts may arise. When more forecasted inventive conceptsare determined, the method branches back to step 1556 where for theinventive concept, forecast implementation elements, implementationmechanisms, and implementation variants are forecasted.

When more forecasted inventive concepts are not determined at step 1566,the method continues with step 1568 where it is determined whether moreforecasted problems exist. As new data is ingested, new problems mayarise. When more forecasted problems are determined, the method branchesback to step 1554 where for a problem, inventive concept(s) forpotentially solving the problem are forecasted. When more forecastedproblems are not determined at step 1568, the method continues with step1570 where it is determined whether more forecasted technical challengesexist.

When more forecasted technical challenges are determined, the methodbranches back to step 1552 where for a technical challenge, problem(s)to be solved are forecasted. When more forecasted technical challengesare not determined at step 1570, the method continues with step 1572where forecasted technical challenges, problems, inventive concepts, andinventive embodiments are compiled. The compilation provides the growthand expense co-processor with a mechanism for determining the totalnumber of inventions to be created over the life of an MTU and amechanism to target particular inventions.

FIG. 199 is a diagram of an example of estimated total number ofinventions, ideal number of inventions, and desired number of inventionsto protect for an MTU (market-tech unit) over the life of the MTU. Thetechnology life of the MTU includes a create, deploy, optimize, mature,and decline phase. In this example, each phase ranges from approximatelytwo and a half to three and a half periods. For example, a period may beone year. The create phase spans a current period (CP), a first nextperiod (1NP), and approximately half of a second next period (2NP). Thedeploy phase spans the latter half of the second next period (2NP), athird next period (3NP), and a fourth next period (4NP).

The optimize phase spans a fifth next period (5NP), a sixth next period(6NP), a seventh next period (7NP), and approximately half of an eighthnext period (8NP). The mature phase spans the latter half of the eighthnext period (8NP), a ninth next period (9NP), a tenth next period(10NP), and approximately half of an eleventh next period (11NP). Thedecline phase spans the latter half of the eleventh next period (11NP),a twelfth next period (12NP), and a thirteenth next period (13NP) (e.g.,the technology life is approximately 14 years when the period is ayear).

The black curve represents the estimated total number of inventions foran MTU. For example, the estimated total number of inventions may becalculated based on comparable existing MTUs as discussed with referenceto FIG. 197 and/or based on developing an inventive embodiment chain asdiscussed with reference to FIG. 198 .

The red curve represents the ideal number of inventions to protect. Theideal number of inventions is based on the total number of inventionsthat warrant patent protection (e.g., have value in a patent fenceprotecting the quantified technology; a patent fence is discussed indetail with reference to subsequent figures) and/or are will likely beprotected industry wide. The ideal number of inventions will typicallybe in the range of 60% to 95% of the total estimated number ofinventions.

The blue curve represents the desired number of inventions to protect.The desired number of inventions to protect is based on a desired patentposition with respect to others. The patent position ranges from weak tosuperior on a sliding scale. A superior patent position corresponds to avery high probability of a favorable outcoming in a patent disputeinvolving the quantified technology. A weak patent position correspondsto a very high probability of an unfavorable outcoming in a patentdispute involving the quantified technology. A superior patent positionincludes actual inventions patent protected in the range of 35% to 80%of the ideal number of inventions.

All curves follow a similar path where the number of inventions climbssteadily in the create phase, drops slightly/remains constant in thedeploy phase, increases significantly towards the end of the optimizephase, decreases significantly in the mature phase, and then drops tozero in or by the decline phase. Mapping the number of inventions overthe life of a technology determines which periods require more funding,prosecution, and preparation.

FIG. 200 is a diagram of another example of estimated total number ofinventions, ideal number of inventions, and desired number of inventionsto protect for an MTU (market-tech unit) over the life of the MTU ifpatent protecting inventions started late the deploy phase. In thisexample, the current period (CP) begins during the middle to end of adeploy phase of an MTU and ends in the beginning of the optimize phase.The optimize phase spans the end of the current period, a first nextperiod (1NP), a second next period (2NP), and a third next period (3NP).The mature phase spans a fourth next period (4NP), a fifth next period(5NP), a sixth next period (6NP), and a portion of a seventh next period(7NP). The decline phase spans the majority of the seventh next period(7NP), and an eighth next period (8NP) (e.g., patent protection occursfor 8 years of an MTU's technology life when the period is a year).

Because patent protection occurs later in the MTU's technology life incomparison to the example of FIG. 199 , the desired number of protectedinventions (e.g., the blue curve) may need to be adjusted to catch up tothe ideal and estimated total invention curves. For example, the bluecurve here follows more closely to the ideal curve (e.g., the red curve)than in FIG. 199 . Shifting the desired number of inventions protectedcloser to the ideal number of patents protected helps the portfolio“catch up” to where it would be if patenting had begun earlier in thelife of the technology.

FIG. 201 is a diagram of an example of a prosecution forecasting timingwindows for a patent application filed in the current period as used bya growth and expense co-processor of an improved computer fortechnology. The prosecution forecasting timeline includes a series ofperiods (e.g., years). For example, the prosecution forecasting timelineincludes a current period, a first next period, a second next period, athird next period, a fourth next period, a fifth next period, and asixth next period. More or less periods are possible based on thedesired forecasting.

The growth and expense co-processor forecasts when prosecution matters(e.g., receipt of a first office action after a new filing, receipt of asecond office action, etc.) will likely occur based on programmable timeframes. The programmable time frames may be based on past performance,industry averages, default settings, and/or details of the prosecution(e.g., whether prioritized/expedited prosecution avenues were pursued,whether certain art areas have longer response times, etc.). Theprogrammable time frames may be continually updated based on newlyingested data.

A programmable time frame (β) is the estimated time between filing a newapplication (i.e., the filing date) and receiving a first office action.The forecasting occurs on a per patent application basis or based on anaverage filing date for new applications. In this example, a newapplication has a filing date that occurs in the middle of the currentperiod, and the programmable time frame (β) spans to the end of thefirst next period (e.g., the programmable time frame (β) isapproximately a year and a half long when a period is a year).

The next programmable time frame (σ) is a first office action window.The first office action window is the time period where receiving afirst office action is likely. In this example, the programmable timeframe (σ) occurs at the beginning of a second next period and lastsabout three quarters of the second next period (e.g., the programmabletime frame (σ) is approximately nine months when a period is a year).

The next programmable time frame (δ) is an estimated time frame betweenreceiving office actions. In this example, the programmable time frame(δ) occurs after each office action window and lasts approximatelysix-seven months when a period is a year. The next programmable timeframe (ε) is the time window of subsequent office actions (e.g., officeactions received after a first office action). The subsequent officeaction window is a time period where receiving a subsequent officeaction is likely. The programmable time frame (ε) may be shorter orlonger than the programmable time frame (σ) where receiving a firstoffice action is likely.

In this example, a programmable time frame (δ) occurs after the firstoffice action window (at about approximately three quarters through thesecond next period) and ends when a second office action window beginsat about a third of the way into the third next period. A programmabletime frame (ε) for the second office action window occurs after theprogrammable time frame (δ) and lasts until approximately a twelfth intothe fourth next period (e.g., the programmable time frame (ε) isapproximately nine months when a period is a year).

A next programmable time frame (δ) occurs after the second office actionwindow (at about approximately a twelfth into the fourth next period)and ends when a third office action window begins at a half of the wayinto the fourth next period. A programmable time frame (ε) for the thirdoffice action window occurs after the programmable time frame (δ) andlasts until approximately a quarter into the fifth next period (e.g.,the programmable time frame (ε) is approximately nine months when aperiod is a year).

A next programmable time frame (δ) occurs after the third office actionwindow (at about approximately a third into the fifth next period) andends when a fourth office action window begins at approximatelyeleven-twelfths of the way into the fifth next period. A programmabletime frame (ε) for the fourth office action window occurs after theprogrammable time frame (δ) and lasts until approximately a two-thirdsof the way into the sixth next period (e.g., the programmable time frame(ε) is approximately nine months when a period is a year). Theprosecution forecasting may be forecasted for longer or shorter than sixnext periods and depends on the technology, the phase of the technology,and the amount of forecasting desired.

FIG. 202 is a diagram of an example of prosecution forecastingparameters as determined and used by a growth and expense co-processorof an improved computer for technology. The particular actions forportfolio matter of office actions shown include a receive first officeaction allowance, a receive first office action, allowed after firstoffice action response, receive second office action, allowed aftersecond office action response, receive third office action, allowedafter third office action response, receive fourth office action,allowed after fourth office action response, and receive another officeaction.

Before receiving a first office action, each of these actions includes areceive probability. The receive probabilities may be historical databased data entries, default settings, and/or calculated based on otherreceive probabilities. Algorithms are used to calculate historical datapoints per client, per tech class, and/or per market-tech unit. In thisexample, the receive first office action allowance has a historical databased data entry of a 5% receive probability and the receive firstoffice action has a historical data based data entry of a 95% receiveprobability. The allowed after first office action response has ahistorical data based data entry of a 66.7% receive probability.

The receive second office action has a calculated receive probability of31.64% ((1—first office action allowance receive probability(5%))×(1-after first office action allowance probability (66.7)) andallowed after second office action response has a historical data baseddata entry of a 66.7% receive probability. The receive third officeaction has a calculated receive probability of 10.53% (received secondoffice action probability (31.64%)×(1—after second office actionallowance probability (66.7%)), and allowed after third office actionresponse has a historical data based data entry of a 66.7% receiveprobability.

The receive fourth office action has a calculated receive probability of3.51% (received third office action probability (10.53%)×(1—after thirdoffice action allowance probability (66.7%)), and allowed after fourthoffice action response has a historical data based data entry of a 66.7%receive probability. The receive another office action has a calculatedreceive probability of 1.17% (received third office action probability(5.51%)×(1—after third office action allowance probability (66.7%)).

FIG. 203 is a diagram of an example of prosecution forecasting timingwindows for a first patent application filed in the current period basedon the timing windows of FIG. 201 . The prosecution forecasting timelineincludes a series of periods (e.g., years). For example, the prosecutionforecasting timeline includes a current period, a first next period, asecond next period, a third next period, a fourth next period, a fifthnext period, and a sixth next period. More or less periods are possiblebased on the desired forecasting.

The growth and expense co-processor forecasts when prosecution matters(e.g., receipt of a first office action after a new filing, receipt of asecond office action, etc.) will likely occur based on programmable timeframes. The programmable time frames may be based on past performance,industry averages, default settings, and/or details of the prosecution(e.g., whether prioritized/expedited prosecution avenues were pursued,whether certain art areas have longer response times, etc.). Theprogrammable time frames may be continually updated based on newlyingested data.

A programmable time frame (β) is the estimated time between filing a newapplication (i.e., the filing date) and receiving a first office action.The forecasting occurs on a per patent application basis or based on anaverage filing date for new applications. In this example, a newapplication (e.g., a first patent application) has a filing date thatoccurs in the middle of the current period, and the programmable timeframe (β) spans to the end of the first next period (e.g., theprogrammable time frame (β) is approximately a year and a half long whena period is a year).

The next programmable time frame (σ) is a first office action window.The first office action window is the time period where receiving afirst office action is likely. In this example, the programmable timeframe (σ) occurs at the beginning of a second next period and lastsabout three quarters of the second next period (e.g., the programmabletime frame (σ) is approximately nine months when a period is a year).

The next programmable time frame (δ) is an estimated time frame betweenreceiving office actions. In this example, the programmable time frame(δ) occurs after each office action window and lasts approximatelysix-seven months when a period is a year. The next programmable timeframe (ε) is the time window of subsequent office actions (e.g., officeactions received after a first office action). The subsequent officeaction window is a time period where receiving a subsequent officeaction is likely. The programmable time frame (ε) may be shorter orlonger than the programmable time frame (σ) where receiving first officeaction window is likely.

In this example, a programmable time frame (δ) occurs after the firstoffice action window (at about approximately three quarters through thesecond next period) and ends when a second office action window beginsat about a third of the way into the third next period. A programmabletime frame (ε) for the second office action window occurs after theprogrammable time frame (δ) and lasts until approximately a twelfth intothe fourth next period (e.g., the programmable time frame (ε) isapproximately nine months when a period is a year).

A next programmable time frame (δ) occurs after the second office actionwindow (at about approximately a twelfth into the fourth next period)and ends when a third office action window begins at a half of the wayinto the fourth next period. A programmable time frame (ε) for the thirdoffice action window occurs after the programmable time frame (ε) andlasts until approximately a quarter into the fifth next period (e.g.,the programmable time frame (ε) is approximately nine months when aperiod is a year).

A next programmable time frame (δ) occurs after the third office actionwindow (at about approximately a third into the fifth next period) andends when a fourth office action window begins at approximatelyeleven-twelfths of the way into the fifth next period. A programmabletime frame (ε) for the fourth office action window occurs after theprogrammable time frame (δ) and lasts until approximately a two-thirdsof the way into the sixth next period (e.g., the programmable time frame(ε) is approximately nine months when a period is a year). Theprosecution forecasting may be forecasted for longer or shorter than sixnext periods and depends on the technology, the phase of the technology,and the amount of forecasting desired.

FIG. 204 is a diagram of an example of forecasted probabilities of whenoffice actions for the first patent application will be received asdetermined by a growth and expense co-processor of an improved computerfor technology. With reference to the office action (OA) windows of FIG.203 , for a patent application filed in a current period, for thecurrent period (CP) and the first next period (1NP), there is zeropercent probability of receiving an office action (e.g., there is a zeropercent probability of receiving an OA if the OA window open date isgreater than a period close date). For a second next period, there is100% chance of receiving a first office action (e.g., there is 100%probability of receiving an OA if the OA window open date is greaterthan the period open date AND the OA window close date is less than theperiod close date).

For a third next period (3NP), there is an 80% chance of receiving asecond office action (e.g., there is an x % probability of receiving anOA if the OA window open date is less than the period close date, the“x”=(period close date— OA window open date)/Duration of the OAwindow)). For a fourth next period (4NP), there is a 20% chance ofreceiving a second office action (e.g., there is a y % probability ofreceiving an OA if the OA window open date is less than the period closedate, the “y”=(OA window close date—period open date)/Duration of the OAwindow)). For a fourth next period (4NP), there is a 50% chance ofreceiving a third office action (e.g., there is an x % probability ofreceiving an OA if the OA window open date is less than the period closedate, the “x”=(period close date— OA window open date)/Duration of theOA window)).

For a fifth next period (5NP), there is a 50% chance of receiving athird office action (e.g., there is a y % probability of receiving an OAif the OA window open date is less than the period close date, the“y”=(OA window close date—period open date)/Duration of the OA window)).For a fifth next period (5NP), there is a 10% chance of receiving afourth office action (e.g., there is an x % probability of receiving anOA if the OA window open date is less than the period close date, the“x”=(period close date— OA window open date)/Duration of the OAwindow)).

For a sixth next period (6NP), there is a 90% chance of receiving afourth office action (e.g., there is a y % probability of receiving anOA if the OA window open date is less than the period close date, the“y”=(OA window close date—period open date)/Duration of the OA window)).

FIG. 205 is a diagram of an example of forecasted probabilities of whenoffice actions will be received combined with the forecastedprobabilities of receiving office actions for the first patentapplication as determined by a growth and expense co-processor of animproved computer for technology.

For calculating the probability of an office action, the timingprobability discussed with reference to FIG. 204 is multiplied by thereceive probability as discussed with reference to FIG. 202 . Asdiscussed with reference to FIG. 202 , the receive first office actionallowance has a 5% receive probability, the receive first office actionhas a 95% receive probability, the receive second office action has areceive probability of 31.64%, the receive third office action has areceive probability of 10.53%, the receive fourth office action has areceive probability of 3.51%, and the receive another office action hasa receive probability of 1.17%.

As discussed with reference to FIG. 204 , for the current period (CP)and the first next period (1NP), there is zero percent probability ofreceiving an office action, for a second next period, there is 100%chance of receiving a first office action, for a third next period(3NP), there is an 80% chance of receiving a second office action, for afourth next period (4NP), there is a 20% chance of receiving a secondoffice action and a 50% chance of receiving a third office action, for afifth next period (5NP), there is a 50% chance of receiving a thirdoffice action and a 10% chance of receiving a fourth office action, andfor a sixth next period (6NP), there is a 90% chance of receiving afourth office action.

The probability of receiving any type of office action (OA) in thecurrent period (CP) and in the first next period (1NP) is thus 0%. Theprobability of receiving an office action in the second next period(2NP) is 100% (e.g., there is a 100% probability of receiving the firstoffice action in the second next period). The probability of receiving asecond office action in the third next period (3NP) is 25.3% (e.g.,31.64%×80%=25.3%). There are no other office actions expected in thethird next period therefore the probability of receiving an officeaction in the third next period is 25.3%. The probability of receiving asecond office action in the fourth next period (4NP) is 6.3% (e.g.,31.54%×20%=6.3%) and the probability of receiving a third office actionin the fourth next period is 5.26% (e.g., 10.53%×50%=5.26%). Therefore,the probability of receiving an office action in the fourth next periodis 11.56% (e.g., 6.3%+5.26%=11.56%).

The probability of receiving a third office action in the fifth nextperiod (5NP) is 5.26% (e.g., 10.53%×50%=5.26%) and the probability ofreceiving a fourth office action in the fifth next period is 0.35%(e.g., 3.51%*10%=0.35%). Therefore, the probability of receiving anoffice action in the fifth next period is 5.61% (e.g.,5.26%+0.35%=5.61%).

The probability of receiving a fourth office action in the sixth nextperiod (6NP) is 3.16% (e.g., 3.51%×90%=3.16%). There are no other officeactions expected in the sixth next period therefore the probability ofreceiving an office action in the third next period is 3.16%.

FIG. 206 is a diagram of an example of prosecution forecasting timingwindows for a second patent application having the first office actionwindow within the current period. The prosecution forecasting timelineincludes a series of periods (e.g., years). For example, the prosecutionforecasting timeline includes a current period, a first next period, asecond next period, a third next period, a fourth next period, a fifthnext period, and a sixth next period. More or less periods are possiblebased on the desired forecasting.

The growth and expense co-processor forecasts when prosecution matters(e.g., receipt of a first office action after a new filing, receipt of asecond office action, etc.) will likely occur based on programmable timeframes. The programmable time frames may be based on past performance,industry averages, default settings, and/or details of the prosecution(e.g., whether prioritized/expedited prosecution avenues were pursued,whether certain art areas have longer response times, etc.). Theprogrammable time frames may be continually updated based on newlyingested data.

In this example, a new application (e.g., a second application) wasfiled at some point prior to the current period and a first officeaction window (programmable time frame (σ) occurs within a currentperiod. The first office action window is the time period wherereceiving a first office action is likely. In this example, theprogrammable time frame (σ) starts and ends within the current period(e.g., the programmable time frame (σ) is approximately nine months whena period is a year).

The next programmable time frame (δ) is an estimated time frame betweenreceiving office actions. In this example, the programmable time frame(δ) occurs after each office action window and lasts approximatelysix-seven months when a period is a year. The next programmable timeframe (ε) is the time window of subsequent office actions (e.g., officeactions received after a first office action). The subsequent officeaction window is a time period where receiving a subsequent officeaction is likely. The programmable time frame (ε) may be shorter orlonger than the programmable time frame (σ) where receiving first officeaction window is likely.

In this example, a programmable time frame (δ) occurs after the firstoffice action window (towards the end of the current period) and endswhen a second office action window begins at about a third of the wayinto the first next period. A programmable time frame (ε) for the secondoffice action window occurs after the programmable time frame (δ) andlasts until a quarter of the way into a second next period (e.g., theprogrammable time frame (ε) is approximately nine months when a periodis a year).

A next programmable time frame (δ) occurs after the second office actionwindow (at about approximately a quarter of the way into the second nextperiod) and ends when a third office action window begins at abouttwo-thirds of the way into the second next period. A programmable timeframe (ε) for the third office action window occurs after theprogrammable time frame (δ) and lasts until approximately half way intothe third next period (e.g., the programmable time frame (ε) isapproximately nine months when a period is a year).

A next programmable time frame (δ) occurs after the third office actionwindow (at about approximately half way into the third next period) andends when a fourth office action window begins at approximatelyeleven-twelfths of the way into the third next period. A programmabletime frame (ε) for the fourth office action window occurs after theprogrammable time frame (δ) and lasts until approximately a two-thirdsof the way into the fourth next period (e.g., the programmable timeframe (ε) is approximately nine months when a period is a year).

A next programmable time frame (δ) occurs after the fourth office actionwindow (at about approximately two-thirds of the way into the fourthnext period) and ends when a fifth office action window begins atapproximately one-fourth of the way into the fifth next period. Aprogrammable time frame (ε) for the fifth office action window occursafter the programmable time frame (δ) and lasts until the end of thefifth next period (e.g., the programmable time frame (ε) isapproximately nine months when a period is a year). The prosecutionforecasting may be forecasted for longer or shorter than six nextperiods and depends on the technology, the phase of the technology, andthe amount of forecasting desired.

FIG. 207 is a diagram of an example of forecasted probabilities of whenoffice actions for the second patent application will be received asdetermined by a growth and expense co-processor of an improved computerfor technology based on the timing of FIG. 206 . For a second patentapplication filed at a point prior to a current period, for the currentperiod (CP) there is a 100% chance of receiving a first office action(e.g., there is 100% probability of receiving an OA if the OA windowopen date is greater than the period open date AND the OA window closedata is less than the period close data). For the first next period(1NP) there is an 80% chance of receiving a second office action (e.g.,there is an x % probability of receiving an OA if the OA window opendate is less than the period close date, the “x”=(period close date— OAwindow open date)/Duration of the OA window)).

For a second next period (2NP), there is a 20% chance of receiving asecond office action (e.g., there is a y % probability of receiving anOA if the OA window open date is less than the period close date, the“y”=(OA window close date-period open date)/Duration of the OA window)).For a second next period, there is a 50% chance of receiving a thirdoffice action (e.g., there is an x % probability of receiving an OA ifthe OA window open date is less than the period close date, the“x”=(period close date— OA window open date)/Duration of the OAwindow)).

For a third next period (3NP), there is a 50% chance of receiving athird office action (e.g., there is a y % probability of receiving an OAif the OA window open date is less than the period close date, the“y”=(OA window close date-period open date)/Duration of the OA window)).For a third next period, there is a 10% chance of receiving a fourthoffice action (e.g., (e.g., there is an x % probability of receiving anOA if the OA window open date is less than the period close date, the“x”=(period close date— OA window open date)/Duration of the OAwindow)).

For a fourth next period (4NP), there is a 90% chance of receiving afourth office action (e.g., there is a y % probability of receiving anOA if the OA window open date is less than the period close date, the“y”=(OA window close date-period open date)/Duration of the OA window)).For a fifth next period (5NP), there is a 100% chance of receiving afifth office action (e.g., there is a 100% probability of receiving anOA if the OA window open date is greater than the period close date ANDthe OA window close date is less than the period close date). For asixth next period (6NP), there is a 0% chance of receiving an officeaction (e.g., there is a zero percent chance of receiving an officeaction if the OA window close date is less than the period open date).

FIG. 208 is a diagram of an example of forecasted probabilities of whenoffice actions will be received combined with the forecastedprobabilities of receiving office actions for the second patentapplication as determined by a growth and expense co-processor of animproved computer for technology.

For calculating the probability of an office action, the timingprobability discussed with reference to FIG. 207 is multiplied by thereceive probability as discussed with reference to FIG. 202 . Asdiscussed with reference to FIG. 202 , a receive first office actionallowance has a 5% receive probability, the receive first office actionhas a 95% receive probability, the receive second office action has areceive probability of 31.63%, the receive third office action has areceive probability of 10.53%, the receive fourth office action has areceive probability of 3.51%, and the receive another office action hasa receive probability of 1.17%.

As discussed with reference to FIG. 207 , for the current period (CP)there is a 100% chance of receiving a first office action, for the firstnext period (1NP) there is an 80% chance of receiving a second officeaction, for a second next period (2NP) there is a 20% chance ofreceiving a second office action and a 50% chance of receiving a thirdoffice action, for a third next period (3NP) there is a 50% chance ofreceiving a third office action and a 10% chance of receiving a fourthoffice action, for a fourth next period (4NP) there is a 90% chance ofreceiving a fourth office action, for a fifth next period (5NP) there isa 100% chance of receiving a fifth office action, and for a sixth nextperiod (6NP), there is a 0% chance of receiving an office action.

The probability of receiving an office action (OA) in the current period(CP) is 100% (e.g., there is a 100% probability of receiving the firstoffice action in the current period). The probability of receiving asecond office action in the first next period (1NP) is 25.3% (e.g.,31.64%×80%=25.3%). There are no other office actions expected in thefirst next period therefore the probability of receiving an officeaction in the first next period is 25.3%.

The probability of receiving a second office action in the second nextperiod (2NP) is 6.3% (e.g., 31.54%×20%=6.3%). The probability ofreceiving a third office action in the second next period is 5.26%(e.g., 10.53%×50%=5.26%). Therefore, the probability of receiving anoffice action in the second next period is 11.56% (e.g.,6.3%+5.26%=11.56%).

The probability of receiving a third office action in the third nextperiod (3NP) is 5.26% (e.g., 10.53%×50%=5.26%) and the probability ofreceiving a fourth office action in the third next period is 0.35%(e.g., 3.51%*10%=0.35%). Therefore, the probability of receiving anoffice action in the third next period is 5.61% (e.g.,5.26%+0.35%=5.61%).

The probability of receiving a fourth office action in the fourth nextperiod (4NP) is 3.16% (e.g., 3.51%×90%=3.16%). There are no other officeactions expected in the fourth next period therefore the probability ofreceiving an office action in the third next period is 3.16%. Theprobability of receiving a fifth office action in the fifth next period(5NP) is 1.17% (e.g., 100%×1.17%=1.17%). There are no other officeactions expected in the fifth next period therefore the probability ofreceiving an office action in the fifth next period is 1.17%. There areno office actions expected in the sixth next period therefore theprobability of receiving an office action in the sixth next period is0%.

FIG. 209 is a diagram of an example of prosecution forecasting timingwindows for a patent application (e.g., a third patent application)having the second office action window being open in the first andsecond next periods and response to the first office action was filedduring the current period. The prosecution forecasting timeline includesa series of periods (e.g., years). For example, the prosecutionforecasting timeline includes a current period, a first next period, asecond next period, a third next period, a fourth next period, a fifthnext period, and a sixth next period. More or less periods are possiblebased on the desired forecasting.

The growth and expense co-processor forecasts when prosecution matters(e.g., receipt of a second office action, etc.) will likely occur basedon programmable time frames. The programmable time frames may be basedon past performance, industry averages, default settings, and/or detailsof the prosecution (e.g., whether prioritized/expedited prosecutionavenues were pursued, whether certain art areas have longer responsetimes, etc.). The programmable time frames may be continually updatedbased on newly ingested data.

In this example, a patent application having the second office actionwindow being open in the first and second next periods and response tothe first office action was filed during the current period. Aprogrammable time frame (ψ) is a time period between filing a firstoffice action response and receiving a second office action (2^(nd) OAwindow begins). In this example, the programmable time frame (ψ) beginsat about half way through a current period and ends about a third of theway into the first next period (e.g., the programmable time frame ψ maybe around 10 months long when a period is a year).

The next programmable time frame (ε) is an OA time window. The officeaction time window is a time period where receiving an office action islikely. A programmable time frame (ε) for the second office actionwindow occurs after the programmable time frame (ψ) and lasts until aone-sixth of the way into a second next period (e.g., the programmabletime frame (ε) may be around 9-10 months when a period is a year).

The next programmable time frame (δ) is an estimated time frame betweenreceiving office actions. In this example, the programmable time frame(δ) occurs after each office action window and lasts approximatelysix-seven months when a period is a year.

In this example, a programmable time frame (δ) occurs after the secondoffice action window (about one-sixth of the way into the second nextperiod) and ends when a third office action window begins at abouttwo-thirds of the way into the second next period. A programmable timeframe (ε) for the third office action window occurs after theprogrammable time frame (δ) and lasts until about half way into a thirdnext period (e.g., the programmable time frame (ε) is approximately 9-10months when a period is a year).

A next programmable time frame (δ) occurs after the third office actionwindow (at about approximately half way into the third next period) andends when a fourth office action window begins at about eleven-twelfthsof the way into the third next period. A programmable time frame (ε) forthe fourth office action window occurs after the programmable time frame(δ) and lasts until approximately two-thirds of the way into the fourthnext period (e.g., the programmable time frame (ε) is approximately 9-10months when a period is a year).

A next programmable time frame (δ) occurs after the third office actionwindow (at about approximately half way into the third next period) andends when a fourth office action window begins at approximatelyeleven-twelfths of the way into the third next period. A programmabletime frame (ε) for the fourth office action window occurs after theprogrammable time frame (δ) and lasts until approximately a two-thirdsof the way into the fourth next period (e.g., the programmable timeframe (ε) is approximately 9-10 months when a period is a year).

A next programmable time frame (δ) occurs after the fourth office actionwindow (at about approximately two-thirds of the way into the fourthnext period) and ends when a fifth office action window begins atapproximately one-fourth of the way into the fifth next period. Aprogrammable time frame (ε) for the fifth office action window occursafter the programmable time frame (δ) and lasts until the end of thefifth next period (e.g., the programmable time frame (ε) isapproximately 9-10 months when a period is a year). The prosecutionforecasting may be forecasted for longer or shorter than six nextperiods and depends on the technology, the phase of the technology, andthe amount of forecasting desired.

FIG. 210 is a diagram of an example of updated prosecution forecastingparameters as determined and used by a growth and expense co-processorof an improved computer for technology based on the timing of FIG. 209 .The particular actions for portfolio matter of office actions showninclude a receive first office action allowance, a receive first officeaction, allowed after first office action response, receive secondoffice action, allowed after second office action response, receivethird office action, allowed after third office action response, receivefourth office action, allowed after fourth office action response, andreceive another office action.

In comparison to the example of FIG. 202 where a first office action hasyet to be received, here, the office action (OA) receive probabilitiesare adjusted based on the fact that an office action has been receivedand a response was filed. The receive probabilities may be historicaldata based data entries, default settings, and/or calculated based onother receive probabilities. Algorithms are used to calculate historicaldata points per client, per tech class, and/or per market-tech unit.

In this example, the receive first office action allowance is adjustedto 0% because it is now known that that possible outcome did not occur.The receive first office action is adjusted to 0% because it is anoutcome that has already occurred and will not occur again. The allowedafter first office action response has a historical data based dataentry of a 66.7% receive probability.

The receive second office action has a calculated receive probability of33.33% ((1—allowed after first office action response receiveprobability (66.7)) and allowed after second office action response hasa historical data based data entry of a 66.7% receive probability. Thereceive third office action has a calculated receive probability of11.1% (received second office action probability (33.3%)×(1—after secondoffice action allowance probability (66.7%)), and allowed after thirdoffice action response has a historical data based data entry of a 66.7%receive probability.

The receive fourth office action has a calculated receive probability of3.7% (received third office action probability (11.1%)×(1—after thirdoffice action allowance probability (66.7%)), and allowed after fourthoffice action response has a historical data based data entry of a 66.7%receive probability. The receive another office action has a calculatedreceive probability of 1.2% (received third office action probability(3.7%)×(1—after third office action allowance probability (66.7%)).

FIG. 211 is a diagram of an example of prosecution forecasting timingwindows for a third patent application having the second office actionwindow being open in the first and second next periods and response tothe first office action was filed during the current period. FIG. 211 issimilar to the diagram of FIG. 209 . The programmable time frame (ψ) isa time period between filing a first office action response andreceiving a second office action (2^(nd) OA window begins). In thisexample, the programmable time frame (ψ) begins at about half waythrough a current period and ends about a third of the way into thefirst next period (e.g., the programmable time frame ψ may be around 10months long when a period is a year).

The next programmable time frame (ε) is an OA time window. The officeaction time window is a time period where receiving an office action islikely. A programmable time frame (ε) for the second office actionwindow occurs after the programmable time frame (ψ) and lasts until aone-sixth of the way into a second next period (e.g., the programmabletime frame (ε) may be around 9-10 months when a period is a year).

The next programmable time frame (δ) is an estimated time frame betweenreceiving office actions. In this example, the programmable time frame(δ) occurs after each office action window and lasts approximatelysix-seven months when a period is a year.

In this example, a programmable time frame (δ) occurs after the secondoffice action window (about one-sixth of the way into the second nextperiod) and ends when a third office action window begins at abouttwo-thirds of the way into the second next period. A programmable timeframe (ε) for the third office action window occurs after theprogrammable time frame (δ) and lasts until about half way into a thirdnext period (e.g., the programmable time frame (ε) is approximately 9-10months when a period is a year).

A next programmable time frame (δ) occurs after the third office actionwindow (at about approximately half way into the third next period) andends when a fourth office action window begins at about eleven-twelfthsof the way into the third next period. A programmable time frame (ε) forthe fourth office action window occurs after the programmable time frame(δ) and lasts until approximately two-thirds of the way into the fourthnext period (e.g., the programmable time frame (ε) is approximately 9-10months when a period is a year).

A next programmable time frame (δ) occurs after the third office actionwindow (at about approximately half way into the third next period) andends when a fourth office action window begins at approximatelyeleven-twelfths of the way into the third next period. A programmabletime frame (ε) for the fourth office action window occurs after theprogrammable time frame (δ) and lasts until approximately a two-thirdsof the way into the fourth next period (e.g., the programmable timeframe (ε) is approximately 9-10 months when a period is a year).

A next programmable time frame (δ) occurs after the fourth office actionwindow (at about approximately two-thirds of the way into the fourthnext period) and ends when a fifth office action window begins atapproximately one-fourth of the way into the fifth next period. Aprogrammable time frame (ε) for the fifth office action window occursafter the programmable time frame (δ) and lasts until the end of thefifth next period (e.g., the programmable time frame (ε) isapproximately 9-10 months when a period is a year). The prosecutionforecasting may be forecasted for longer or shorter than six nextperiods and depends on the technology, the phase of the technology, andthe amount of forecasting desired.

FIG. 212 is a diagram of an example of forecasted probabilities of whenoffice actions for the third patent application will be received asdetermined by a growth and expense co-processor of an improved computerfor technology. With reference to the office action (OA) windows of FIG.211 , for a third patent application where an office action response isfiled in a current period, there is a 0% probability of receiving anoffice action (OA) for the current period (CP) (e.g., there is a zeropercent probability of receiving an OA if the OA window open date isgreater than a period close date). For a first next period (1NP), thereis 80% chance of receiving a second office action (e.g., there is an x %probability of receiving an OA if the OA window open date is less thanthe period close date, the “x”=(period close date— OA window opendate)/Duration of the OA window)).

For a second next period (2NP), there is an 20% chance of receiving asecond office action (e.g., there is a y % probability of receiving anOA if the OA window open date is less than the period close date, the“y”=(OA window close date—period open date)/Duration of the OA window)).For the second next period, there is an 50% chance of receiving a thirdoffice action (e.g., there is an x % probability of receiving an OA ifthe OA window open date is less than the period close date, the“x”=(period close date— OA window open date)/Duration of the OAwindow)).

For a third next period (3NP), there is a 50% chance of receiving athird office action (e.g., there is a y % probability of receiving an OAif the OA window open date is less than the period close date, the“y”=(OA window close date—period open date)/Duration of the OA window)).For the third next period, there is a 10% chance of receiving a fourthoffice action ((e.g., there is an x % probability of receiving an OA ifthe OA window open date is less than the period close date, the “x”=(period close date— OA window open date)/Duration of the OA window)).

For a fourth next period (4NP), there is a 90% chance of receiving afourth office action (e.g., there is a y % probability of receiving anOA if the OA window open date is less than the period close date, the“y”=(OA window close date—period open date)/Duration of the OA window)).For a fifth next period (5NP), there is a 100% chance of receiving afifth office action (e.g., there is 100% probability of an OA is the OAwindow open date is less greater than the period open date AND the OAwindow close date is less than the period close date)). For a sixth nextperiod (6NP), there is a 0% chance of receiving an office action (e.g.,there is a 0% probability of an office action is the OA window closedate is less than the period open date).

FIG. 213 is a diagram of an example of forecasted probabilities of whenoffice actions will be received combined with the forecastedprobabilities of receiving office actions for the third patentapplication as determined by a growth and expense co-processor of animproved computer for technology. For calculating the probability of anoffice action, the timing probability discussed with reference to FIG.212 is multiplied by the receive probability as discussed with referenceto FIG. 210 . As discussed with reference to FIG. 210 the receive secondoffice action has a receive probability of 33.3%, the receive thirdoffice action has a receive probability of 11.1%, the receive fourthoffice action has a receive probability of 3.7%, and the receive anotheroffice action has a receive probability of 1.2%.

As discussed with reference to FIG. 212 , for the current period (CP)there is a 0% chance of an office action, for the first next period(1NP) there is an 80% chance of receiving a second office action, for asecond next period (2NP) there is a 20% chance of receiving a secondoffice action and a 50% chance of receiving a third office action, for athird next period (3NP) there is a 50% chance of receiving a thirdoffice action and a 10% chance of receiving a fourth office action, fora fourth next period (4NP) there is a 90% chance of receiving a fourthoffice action, for a fifth next period (5NP) there is a 100% chance ofreceiving a fifth office action, and for a sixth next period (6NP),there is a 0% chance of receiving an office action.

The probability of receiving an office action (OA) in the current period(CP) is 0%. The probability of receiving a second office action in thefirst next period (1NP) is 26.7% (e.g., 33.3%×80%=26.7%). There are noother office actions expected in the first next period therefore theprobability of receiving an office action in the first next period is26.7%.

The probability of receiving a second office action in the second nextperiod (2NP) is 6.7% (e.g., 33.3%×20%=6.7%). The probability ofreceiving a third office action in the second next period is 5.5% (e.g.,11.1%×50%=5.5%). Therefore, the probability of receiving an officeaction in the second next period is 12.2% (e.g., 6.7%+5.5%=12.2%).

The probability of receiving a third office action in the third nextperiod (3NP) is 5.5% (e.g., 11.1%×50%=5.5%) and the probability ofreceiving a fourth office action in the third next period is 0.37%(e.g., 3.7%*10%=0.37%). Therefore, the probability of receiving anoffice action in the third next period is 5.87% (e.g.,5.5%+0.37%=5.87%).

The probability of receiving a fourth office action in the fourth nextperiod (4NP) is 3.3% (e.g., 3.7%×90%=3.3%). There are no other officeactions expected in the fourth next period therefore the probability ofreceiving an office action in the fourth next period is 3.3%. Theprobability of receiving a fifth office action in the fifth next period(5NP) is 1.17% (e.g., 1.2%×100%=1.2%). There are no other office actionsexpected in the fifth next period therefore the probability of receivingan office action in the fifth next period is 1.2%. There are no officeactions expected in the sixth next period therefore the probability ofreceiving an office action in the sixth next period is 0%.

FIG. 214 is a diagram of an example of prosecution forecasting timingwindows for a patent application (e.g., a fourth patent application)that is forecasted to be filed in the first next period. The prosecutionforecasting timeline includes a series of periods (e.g., years). Forexample, the prosecution forecasting timeline includes a current period,a first next period, a second next period, a third next period, a fourthnext period, a fifth next period, and a sixth next period. More or lessperiods are possible based on the desired forecasting.

The growth and expense co-processor forecasts when prosecution matters(e.g., receipt of a first office action after a new filing, receipt of asecond office action, etc.) will likely occur based on programmable timeframes. The programmable time frames may be based on past performance,industry averages, default settings, and/or details of the prosecution(e.g., whether prioritized/expedited prosecution avenues were pursued,whether certain art areas have longer response times, etc.). Theprogrammable time frames may be continually updated based on newlyingested data.

A programmable time frame ((δ) is the estimated time between filing anew application (i.e., the filing date) and receiving a first officeaction. The forecasting occurs on a per patent application basis orbased on an average filing date for new applications. In this example, anew application has a filing date that is projected to occur abouttwo-thirds of the way through a first next period, and the programmabletime frame ((δ) spans to about a third of the way through a third nextperiod (e.g., the programmable time frame ((δ) is approximately a yearand eight months long when a period is a year).

The next programmable time frame (σ) is a first office action window.The first office action window is the time period where receiving afirst office action is likely. In this example, the programmable timeframe (σ) occurs about a third of the way into a third next period andlasts about one-sixth of the way into a fourth next period (e.g., theprogrammable time frame (σ) is approximately 9-10 months when a periodis a year).

The next programmable time frame (δ) is an estimated time frame betweenreceiving office actions. In this example, the programmable time frame(δ) occurs after each office action window and lasts approximatelysix-seven months when a period is a year. The next programmable timeframe (ε) is the time window of subsequent office actions (e.g., officeactions received after a first office action). The subsequent officeaction window is a time period where receiving a subsequent officeaction is likely. The programmable time frame (ε) may be shorter orlonger than the programmable time frame (σ) where receiving first officeaction window is likely.

In this example, a programmable time frame (δ) occurs after the firstoffice action window (at about approximately one-sixth through thefourth next period) and ends when a second office action window beginsat about two-thirds of the way into the fourth next period. Aprogrammable time frame (ε) for the second office action window occursafter the programmable time frame (δ) and lasts until approximatelyhalfway into the fifth next period (e.g., the programmable time frame(ε) is approximately 9-10 months when a period is a year).

A next programmable time frame (δ) occurs after the second office actionwindow (at about approximately halfway into the fifth next period) andends when a third office action window begins at about eleven-twelfthsof the way into the fifth next period. A programmable time frame (ε) forthe third office action window occurs after the programmable time frame(δ) and lasts until approximately two-thirds of the way into the sixthnext period (e.g., the programmable time frame (ε) is approximately 9-10months when a period is a year). The prosecution forecasting may beforecasted for longer or shorter than six next periods and depends onthe technology, the phase of the technology, and the amount offorecasting desired.

FIG. 215 is a diagram of an example of updated prosecution forecastingparameters as determined and used by a growth and expense co-processorof an improved computer for technology based on the timing of FIG. 214 .The particular actions for portfolio matter of office actions showninclude a receive first office action allowance, a receive first officeaction, allowed after first office action response, receive secondoffice action, allowed after second office action response, receivethird office action, allowed after third office action response, receivefourth office action, allowed after fourth office action response, andreceive another office action.

Before receiving a first office action, each of these actions includes areceive probability. The receive probabilities may be historical databased data entries, default settings, and/or calculated based on otherreceive probabilities. Algorithms are used to calculate historical datapoints per client, per tech class, and/or per market-tech unit. In thisexample, the receive first office action allowance has a historical databased data entry of a 5% receive probability and the receive firstoffice action has a historical data based data entry of a 95% receiveprobability. The allowed after first office action response has ahistorical data based data entry of a 66.7% receive probability.

The receive second office action has a calculated receive probability of31.64% ((1—first office action allowance receive probability(5%))×(1-after first office action allowance probability (66.7)) andallowed after second office action response has a historical data baseddata entry of a 66.7% receive probability. The receive third officeaction has a calculated receive probability of 10.53% (received secondoffice action probability (31.64%)×(1-after second office actionallowance probability (66.7%)) and allowed after third office actionresponse has a historical data based data entry of a 66.7% receiveprobability.

The receive fourth office action has a calculated receive probability of3.51% (received third office action probability (10.53%)×(1—after thirdoffice action allowance probability (66.7%)) and allowed after fourthoffice action response has a historical data based data entry of a 66.7%receive probability. The receive another office action has a calculatedreceive probability of 1.17% (received third office action probability(5.51%)×(1—after third office action allowance probability (66.7%)).

FIG. 216 is a diagram of an example of prosecution forecasting timingwindows for a fourth patent application that is forecasted to be filedin the first next period. FIG. 216 is similar to the diagram of FIG. 214and shows a new (e.g., fourth) patent application with a filing dateprojected to occur about two-thirds of the way through a first nextperiod. The programmable time frame ((δ) spans to about a third of theway through a third next period, the first office action time window (σ)occurs about a third of the way into a third next period and lasts aboutone-sixth of the way into a fourth next period.

The next programmable time frame (δ) is an estimated time frame betweenreceiving office actions. In this example, the programmable time frame(δ) occurs after each office action window and lasts approximatelysix-seven months when a period is a year. The next programmable timeframe (ε) is the time window of subsequent office actions (e.g., officeactions received after a first office action). The subsequent officeaction window is a time period where receiving a subsequent officeaction is likely. The programmable time frame (ε) may be shorter orlonger than the programmable time frame (σ) where receiving first officeaction window is likely.

In this example, a programmable time frame (δ) occurs after the firstoffice action window (at about approximately one-sixth through thefourth next period) and ends when a second office action window beginsat about two-thirds of the way into the fourth next period. Aprogrammable time frame (ε) for the second office action window occursafter the programmable time frame (δ) and lasts until approximatelyhalfway into the fifth next period. A next programmable time frame (δ)occurs after the second office action window (at about approximatelyhalfway into the fifth next period) and ends when a third office actionwindow begins at about eleven-twelfths of the way into the fifth nextperiod. A programmable time frame (ε) for the third office action windowoccurs after the programmable time frame (δ) and lasts untilapproximately two-thirds of the way into the sixth next period (e.g.,the programmable time frame (ε) is approximately 9-10 months when aperiod is a year). The prosecution forecasting may be forecasted forlonger or shorter than six next periods and depends on the technology,the phase of the technology, and the amount of forecasting desired.

FIG. 217 is a diagram of an example of forecasted probabilities of whenoffice actions for the fourth patent application will be received asdetermined by a growth and expense co-processor of an improved computerfor technology. With reference to the office action (OA) windows of FIG.216 , for a fourth patent application filed in a first next period, forthe current period (CP), the first next period (1NP), and the secondnext period (2NP) there is zero percent probability of receiving anoffice action (e.g., there is a zero percent probability of receiving anOA if the OA window open date is greater than a period close date).

For a third next period (3NP), there is 90% chance of receiving a firstoffice action (e.g., there is an x % probability of receiving an OA ifthe OA window open date is less than the period close date, the“x”=(period close date— OA window open date)/Duration of the OAwindow)).

For a fourth next period (4NP), there is an 10% chance of receiving afirst office action ((e.g., there is a y % probability of receiving anOA if the OA window open date is less than the period close date, the“y”=(OA window close date—period open date)/Duration of the OA window)).For the fourth next period, there is a 50% chance of receiving a secondoffice action (e.g., there is an x % probability of receiving an OA ifthe OA window open date is less than the period close date, the“x”=(period close date— OA window open date)/Duration of the OAwindow)).

For a fifth next period (5NP), there is a 50% chance of receiving asecond office action ((e.g., there is a y % probability of receiving anOA if the OA window open date is less than the period close date, the“y”=(OA window close date—period open date)/Duration of the OA window)).For a fifth next period, there is a 10% chance of receiving a thirdoffice action (e.g., there is an x % probability of receiving an OA ifthe OA window open date is less than the period close date, the“x”=(period close date— OA window open date)/Duration of the OAwindow)).

For a sixth next period (6NP), there is a 90% chance of receiving athird office action (e.g., there is a y % probability of receiving an OAif the OA window open date is less than the period close date, the“y”=(OA window close date—period open date)/Duration of the OA window)).

FIG. 218 is a diagram of an example of forecasted probabilities of whenoffice actions will be received combined with the forecastedprobabilities of receiving office actions for the fourth patentapplication as determined by a growth and expense co-processor of animproved computer for technology.

For calculating the probability of an office action, the timingprobability discussed with reference to FIG. 217 is multiplied by thereceive probability as discussed with reference to FIG. 215 . Asdiscussed with reference to FIG. 215 , the receive first office actionallowance has a 5% receive probability, the receive first office actionhas a 95% receive probability, the receive second office action has areceive probability of 31.63%, the receive third office action has areceive probability of 10.53%, the receive fourth office action has areceive probability of 3.51%, and the receive another office action hasa receive probability of 1.17%.

As discussed with reference to FIG. 217 , for the current period (CP),the first next period (1NP), and the second next period (2NP) there iszero percent probability of receiving an office action. For a third nextperiod (3NP), there is 90% chance of receiving a first office action.For a fourth next period (4NP), there is an 10% chance of receiving afirst office action and a 50% chance of receiving a second officeaction. For a fifth next period (5NP), there is a 50% chance ofreceiving a second office action and a 10% chance of receiving a thirdoffice action. For a sixth next period (6NP), there is a 90% chance ofreceiving a third office action.

The probability of receiving any type of office action (OA) in thecurrent period (CP), first next period (1NP), and second next period(2NP) is thus 0%. The probability of receiving an office action in thethird next period (3NP) is 90% (e.g., 90%×(95%+5%)=100%). There are noother office actions expected in the third next period therefore theprobability of receiving an office action in the third next period is90%.

The probability of receiving a first office action in the fourth nextperiod (4NP) is 10% (e.g., 10%×(95%+5%)=10%). The probability ofreceiving a second office action in the fourth next period is 15.8%(e.g., 50%×31.64%=15.8%). The probability of receiving an office actionin the fourth next period is 26.8% (e.g., 10%×15.8%=26.8%). Theprobability of receiving a second office action in the fifth next period(5NP) is 15.8% (e.g., 50%×31.64%=15.8%) and the probability of receivinga third office action in the fifth next period is 1.1% (e.g.,10%×10.53%=1.1%). Therefore, the probability of receiving an officeaction in the fifth next period is 16.9% (e.g., 15.8%+1.1%=16.9%).

The probability of receiving a third office action in the sixth nextperiod (6NP) is 9.4% (e.g., 10.53%×90%=9.4%). There are no other officeactions expected in the sixth next period therefore the probability ofreceiving an office action in the third next period is 9.4%.

FIG. 219 is a diagram of an example of combining the prosecutionforecasting of the first through fourth patent applications asdetermined by a growth and expense co-processor of an improved computerfor technology. The OA probabilities for a first patent application (asdiscussed with reference to FIG. 205 ) are 0% for a current period (CP),0% for a first next period, 100% for a second next period (2NP), 25.3%for a third next period (3NP), 11.56% for a fourth next period (4NP),5.61% fora fifth next period (5NP), and 3.16% fora sixth next period(6NP).

The OA probabilities for a second patent application (as discussed withreference to FIG. 208 ) are 100% for a current period (CP), 25.3% for afirst next period, 11.56% for a second next period (2NP), 5.61% for athird next period (3NP), 3.16% for a fourth next period (4NP), 1.17% fora fifth next period (5NP), and 0% for a sixth next period (6NP).

The OA probabilities for a third patent application (as discussed withreference to FIG. 213 ) are 0% for a for a current period (CP), 26.7%for a first next period, 12.2% for a second next period (2NP), 5.87% fora third next period (3NP), 3.3% fora fourth next period (4NP), 1.17%fora fifth next period (5NP), and 0% fora sixth next period (6NP).

The OA probabilities for a fourth patent application (as discussed withreference to FIG. 218 ) are 0% for a for a current period (CP), 0% for afirst next period, 0% for a second next period (2NP), 90% for a thirdnext period (3NP), 26.8% for a fourth next period (4NP), 16.9% forafifth next period (5NP), and 9.4% fora sixth next period (6NP).

Based on the OA probabilities for each patent application, a cumulativesum for OA probabilities for patent applications I-4 over acurrent-sixth period can be calculated. For example, the probability ofreceiving an office action in the current period (CP) is 100% (e.g.,0%+100%+0%+0%=100%). The probability of receiving an office action inthe first next period (1NP) is 52% (e.g., 0%+25.3%+26.7%+0%=52%). Theprobability of receiving an office action in the second next period(2NP) is 123.8% (e.g., 100%+11.56%+12.2%+0%=123.8%). The probability ofreceiving an office action in the third next period (3NP) is 126.8%(e.g., 25.3%+5.61%+5.87%+90%=126.5%). The probability of receiving anoffice action in the fourth next period (4NP) is 44.8% (e.g.,11.56%+3.16%+3.3%+26.8%=44.8%). The probability of receiving an officeaction in the fifth next period (5NP) is 24.9% (e.g.,5.61%+1.17%+1.17%+16.9%=24.9%). The probability of receiving an officeaction in the sixth next period (6NP) is 12.6% (e.g., 3.16%+0%+0%+9.4%=12.6%).

FIG. 220 is a diagram of an example of forecasting the quantity and timeof receiving offices action for the first through fourth patentapplications received per period as determined by a growth and expenseco-processor of an improved computer for technology. From the cumulativesums of the office action probabilities for patent applications #1-#4 ofFIG. 219 for a current through sixth period, a total number of officeactions can be estimated for each period.

During a current period (CP) where the probability of receiving anoffice action (OA) is 100%, one office action can be expected. During afirst next period (1NP) where the probability of receiving an officeaction (OA) is 52%, 0.52 office actions can be expected. During a secondnext period (2NP) where the probability of receiving an office action(OA) is 123.8%, 1.24 office actions can be expected. During a third nextperiod (3NP) where the probability of receiving an office action (OA) is126.8%, 1.27 office actions can be expected. During a fourth next period(4NP) where the probability of receiving an office action (OA) is 44.8%,0.45 office actions can be expected.

During a fifth next period (5NP) where the probability of receiving anoffice action (OA) is 24.9%, 0.25 office actions can be expected. Duringa sixth next period (6NP) where the probability of receiving an officeaction (OA) is 12.6%, 0.13 office actions can be expected.

FIG. 221 is a diagram of an example of forecasting first office actionallowances and non-allowance office actions for the first through fourthpatent applications received per period as determined by a growth andexpense co-processor of an improved computer for technology.

For a current period (CP), the second patent application has a 100%probability of receiving a first office action while the otherapplications have a 0% probability of receiving a first office action.Therefore, the sum probability of receiving a first office action in thecurrent period is 100%. For a first next period (1NP), no applicationshave a probability of receiving a first office action. Therefore, thesum probability of receiving a first office action in the first nextperiod is 0%.

For a second next period (2NP), the first patent application has a 100%probability of receiving a first office action while the otherapplications have a 0% probability of receiving a first office action.Therefore, the sum probability of receiving a first office action in thesecond next period is 100%. For a third next period (3NP), the fourthpatent application has a 90% probability of receiving a first officeaction while the other applications have a 0% probability of receiving afirst office action. Therefore, the sum probability of receiving a firstoffice action in the third next period is 90%.

For a fourth next period (4NP), the fourth patent application has a 10%probability of receiving a first office action while the otherapplications have a 0% probability of receiving a first office action.Therefore, the sum probability of receiving a first office action in thefourth next period is 10%. No applications have a probability ofreceiving a first office action in the fifth or sixth next periodstherefore the sum probability of receiving a first office action in thefifth or sixth next period is 0%.

Based on the probability of first office actions, an amount of firstoffice actions can be estimated. For example, for the current periodwith the 100% of receiving a first office action, one first officeaction can be expected. For the first next period with the 0% ofreceiving a first office action, no first office actions are expected.For the second next period with the 100% of receiving a first officeaction, one first office action can be expected.

For the third next period with the 90% of receiving a first officeaction, 0.9 first office actions are expected. For the fourth nextperiod with the 10% of receiving a first office action, 0.1 first officeaction can be expected. For the fifth next period with the 0% ofreceiving a first office action, no first office actions are expected.For the sixth next period with the 0% of receiving a first officeaction, no first office actions are expected.

In this example, the probability of obtaining a first office actionallowance is 5%. Therefore, with one first office action expected andone total number of office actions (OAs) in the current period, 0.05office action responses are first office action (OA) allowance responsesand 0.95 office action responses full office action responses (e.g., anoffice action response that is not a first office action allowanceresponse).

With zero first office actions and 0.52 total office actions expected inthe first next period, zero office actions are OA allowance responses,and 0.52 office actions are full office action responses. With one firstoffice action and 1.24 total office actions expected in the second nextperiod, 0.05 office actions are OA allowance responses, and 1.19 officeactions are full office action responses. With 0.9 first office actionsand 1.27 total office actions expected in the third next period, 0.045office actions are OA allowance responses (e.g., 5%*0.9), and 1.23office actions are full office action responses.

With 0.1 first office actions and 0.45 total office actions expected inthe fourth next period, 0.005 office actions are OA allowance responses(e.g., 5%*0.1), and 0.44 office actions are full office actionresponses. With zero first office actions and 0.25 total office actionsexpected in the fifth next period, zero office actions are OA allowanceresponses and 0.25 office actions are full office action responses. Withzero first office actions and 0.13 total office actions expected in thesixth next period, zero office actions are OA allowance responses and0.13 office actions are full office action responses.

FIG. 222 is a diagram of an example of forecasting expense for the firstoffice action allowances and non-allowance office actions of FIG. 221 asdetermined by a growth and expense co-processor of an improved computerfor technology.

As discussed with reference to FIG. 221 , 0.05 first office action (OA)allowance responses and 0.95 full office action responses are expectedfor a current period (CP), zero first office action (OA) allowanceresponses and 0.52 full office action responses are expected for a firstnext period (1NP), 0.05 first office action allowance responses and 1.19full office action responses are expected for a second next period(2NP), 0.045 first office action allowance responses and 1.23 fulloffice action responses are expected for a third next period (3NP),0.005 first office action allowance responses and 0.44 full officeaction responses are expected for a fourth next period (4NP), zero firstoffice action allowance responses and 0.25 full office action responsesare expected for a fifth next period (5NP), and zero first office actionallowance responses and 0.13 full office action responses are expectedfor a sixth next period (6NP).

Based on these probabilities, the expenses for OA responses can beestimated. For example, when the expense for a first office actionallowance response is $1000 ($1K) and a full office action response is$5000 ($5K), expenses for a current period (CP) are $4.8K (e.g., $50 for0.05 first office action allowance responses and $4.75K for 0.95 fulloffice action allowance responses. Expenses for a first next period(1NP) are $2.6K (e.g., 0.52 x $5K=$2.6K). Expenses for a second nextperiod (2NP) are $6.0K (e.g., $50 for 0.05 first office action allowanceresponses and $5.95K for 1.19 full office action allowance responses).Expenses for a third next period (3NP) are $6.2K (e.g., $45 for 0.045first office action allowance responses and $6.15K for 1.23 full officeaction allowance responses).

Expenses for a fourth next period (4NP) are $2.2K (e.g., $5 for 0.005first office action allowance responses and $2.2K for 0.44 full officeaction allowance responses). Expenses for a fifth next period (5NP) are$1.25K (e.g., 0.25×$5K=$1.25K). Expenses for a sixth next period (6NP)are $650 (e.g., 0.13×$5K=$650).

FIG. 223 is a diagram of an example of issuance forecasting timingwindows for a patent application (e.g., a first patent application) thatis to be filed in the current period. The issuance forecasting timelineincludes a series of periods (e.g., years). For example, the issuanceforecasting timeline includes a current period, a first next period, asecond next period, a third next period, a fourth next period, a fifthnext period, and a sixth next period. More or less periods are possiblebased on the desired forecasting.

The growth and expense co-processor forecasts when issuances will likelyoccur based on programmable time frames. The programmable time framesmay be based on past performance, industry averages, default settings,and/or details of prosecution (e.g., when office action responses arefiled, etc.). The programmable time frames may be continually updatedbased on newly ingested data.

The forecasting occurs on a per patent application basis or based on anaverage filing date for new applications. In this example, a newapplication has a filing date that occurs in the middle of the currentperiod, and the programmable time frame ((δ) spans to the end of thefirst next period (e.g., the programmable time frame ((δ) isapproximately a year and a half long when a period is a year). If afirst office action allowance occurs, a notice of allowance (NOA) occursat the end of the first next period (after the programmable time frame(δ)).

For this example, office action responses are assumed to be filed in themiddle of an office action (OA) window. For example, a response to firstoffice action is filed in the middle of the second next period after atime β+σ/2(where σ is the time frame of a first office action window).

A programmable time frame (λ) is the time after filing an office actionto receiving a notice of allowance. The programmable time frame (1.5ε)is the time window between filing office action responses (where a isthe time frame of subsequent office action windows). As shown, afterfiling a first office action response after a period of β+σ/2, a noticeof allowance may occur after a time frame λ(e.g., about three-quartersinto the second next period).

If a notice of allowance does not occur after a first office action,after a period of 1.5ε from filing a first office action response, aresponse to a second office action is filed. After filing a secondoffice action response, a notice of allowance may occur after a timeframe λ(e.g., about one-twelfth into the fourth next period).

If a notice of allowance does not occur after a second office action,after a period of 1.5ε from filing a second office action response, aresponse to a third office action is filed. After filing a third officeaction response, a notice of allowance may occur after a time frameλ(e.g., about one-third into the fifth next period).

If a notice of allowance does not occur after a third office action,after a period of 1.5ε from filing a third office action response, aresponse to a fourth office action is filed. After filing a fourthoffice action response, a notice of allowance may occur after a timeframe λ(e.g., about half way into the sixth next period). The issuanceforecasting may be forecasted for longer or shorter than six nextperiods and depends on the technology, the phase of the technology, andthe amount of forecasting desired.

FIG. 224 is a diagram of an example of issuance forecasting parametersas determined and used by a growth and expense co-processor of animproved computer for technology based on the timing of FIG. 223 . Theissuance probability is calculated by multiplying issuance actionreceive probability by an allowance probability. Receive and allowanceprobabilities may be based on historical data, a particular market-techunit, default settings, etc.

Issuance actions (similar to prosecution actions as previouslydiscussed) include a first office action (OA) allowance, a receive firstoffice action, a receive second office action, a receive third officeaction, a receive fourth office action, and a receive another officeaction. The receive probability of a first office action allowance is5%, the receive probability of a first office action is 95%, the receiveprobability of a second office action is 31.64%, the receive probabilityof a third office action is 10.53%, the receive probability of a fourthoffice action is 3.51%, and the receive probability of another officeaction is 1.17%.

If a first office action allowance is received, the allowanceprobability is 100%, if a first office action is received the allowanceprobability is 66.7%, if a second office action is received theallowance probability is 66.7%, if a third office action is received theallowance probability is 66.7%, if a fourth office action is receivedthe allowance probability is 66.7%, and if another office action isreceived the allowance probability is 66.7%.

The issuance probability before receiving a first office action forissuance due to a first office action allowance is 5.0% (e.g., 5%×100%).The issuance probability before receiving a first office action forissuance after receiving a first office action is 63.4% (e.g.,95%×66.7%). The issuance probability before receiving a first officeaction for issuance after receiving a second office action is 21.1%(e.g., 31.64%×66.7%). The issuance probability before receiving a firstoffice action for issuance after receiving a third office action is 7.0%(e.g., 10.53%×66.7%). The issuance probability before receiving a firstoffice action for issuance after receiving a fourth office action is2.3% (e.g., 3.51%×66.7%). The issuance probability before receiving afirst office action for issuance after receiving a fifth office actionis 0.8% (e.g., 1.17%×66.7%).

FIG. 225 is a diagram of an example of issuance forecasting timingwindows for a first patent application that is forecasted to be filed inthe current period. The issuance forecasting timeline is similar to theexample of FIG. 223 where a new application has a filing date thatoccurs in the middle of the current period, and the programmable timeframe ((3) spans to the end of the first next period (e.g., theprogrammable time frame ((δ) is approximately a year and a half longwhen a period is a year). If a first office action allowance occurs, anotice of allowance (NOA) occurs at the end of the first next period(after the programmable time frame (δ)).

For this example, office action responses are assumed to be filed in themiddle of an office action (OA) window. For example, a response to firstoffice action is filed in the middle of the second next period after atime β+σ/2(where σ is the time frame of a first office action window).

A programmable time frame (λ) is the time after filing an office actionto receiving a notice of allowance. The programmable time frame (1.5ε)is the time window between filing office action responses (where a isthe time frame of subsequent office action windows). As shown, afterfiling a first office action response after a period of β+σ/2, a noticeof allowance may occur after a time frame λ(e.g., about three-quartersinto the second next period).

If a notice of allowance does not occur after a first office action,after a period of 1.5ε from filing a first office action response, aresponse to a second office action is filed. After filing a secondoffice action response, a notice of allowance may occur after a timeframe λ(e.g., about one-twelfth into the fourth next period).

If a notice of allowance does not occur after a second office action,after a period of 1.5ε from filing a second office action response, aresponse to a third office action is filed. After filing a third officeaction response, a notice of allowance may occur after a time frameλ(e.g., about one-third into the fifth next period).

If a notice of allowance does not occur after a third office action,after a period of 1.5ε from filing a third office action response, aresponse to a fourth office action is filed. After filing a fourthoffice action response, a notice of allowance may occur after a timeframe λ(e.g., about half way into the sixth next period). The issuanceforecasting may be forecasted for longer or shorter than six nextperiods and depends on the technology, the phase of the technology, andthe amount of forecasting desired.

FIG. 226 is a diagram of an example of forecasted probabilities of whena notice of allowance for the first patent application will be receivedas determined by a growth and expense co-processor of an improvedcomputer for technology. In light of the timing windows discussed withreference to FIG. 225 , timing probabilities for issuance can becalculated for a period. The dates for potential notices of allowance(NOAs) can be calculated and then the period those dates are in aredetermined. For example, with a first patent application filed in acurrent period (CP), there is zero percent probability of issuance inthe current period or the first next period (1NP). If a NOA is receivedfrom a first office action allowance, there is a 100% probability ofissuance during a second next period (2NP). If a NOA is received from afirst office action response, there is a 100% probability of issuanceduring the second next period.

If a NOA is received from a second office action response, there is a100% probability of issuance during a fourth next period (4NP). If a NOAis received from a third office action response, there is a 100%probability of issuance during the fifth next period (5NP). If a NOA isreceived from a fourth office action response, there is a 100%probability of issuance during the sixth next period (6NP).

FIG. 227 is a diagram of an example of forecasted probabilities of whena notice of allowance will be received combined with the forecastedprobabilities of receiving a notice of allowance for the first patentapplication as determined by a growth and expense co-processor of animproved computer for technology. To determine the timing probabilitiesfor issuance, the issuance probabilities based on office action (OA) aremultiplied by the timing probabilities for issuance in a period.

The issuance probabilities based on office action were discussed withreference to FIG. 224 . The issuance probability due to a first officeaction allowance is 5.0%, the issuance probability after receiving afirst office action is 63.4%, the issuance probability after receiving asecond office action is 21.1%. The issuance probability after receivinga third office action is 7.0%. The issuance probability after receivinga fourth office action is 2.3%. The issuance probability after receivinga fifth office action is 0.8%.

The timing probabilities for issuance in a period were discussed withreference to FIG. 226 . With a first patent application filed in acurrent period (CP), there is zero percent probability of issuance inthe current period or the first next period (1 NP). If a NOA is receivedfrom a first office action allowance, there is a 100% probability ofissuance during a second next period (2NP). If a NOA is received from afirst office action response, there is a 100% probability of issuanceduring the second next period. If a NOA is received from a second officeaction response, there is a 100% probability of issuance during a fourthnext period (4NP). If a NOA is received from a third office actionresponse, there is a 100% probability of issuance during the fifth nextperiod (5NP). If a NOA is received from a fourth office action response,there is a 100% probability of issuance during the sixth next period(6NP).

As such, with a first patent application filed in a current period (CP),there is zero percent probability of issuance in the current period orthe first next period (1NP). There is a 5% probability of issuanceduring a second next period (2NP) due to a receive NOA from a firstoffice action allowance (e.g., 5%×100%=5%). There is a 63.4% probabilityof issuance during a second next period due to a receive NOA from afirst office action response (e.g., 63.4%×100%=63.4%). The sum of theallowance/issuance probability for the second next period is thus 68.4%(e.g., 5%+63.4%=68.4%).

There is zero percent probability of issuance in a third next period(3NP). There is a 21.1% probability of issuance during a fourth nextperiod (4NP) due to a receive NOA from a second office action response(e.g., 21.1%×100%=21.1%). The sum of the allowance/issuance probabilityfor the fourth next period is 21.1%. There is a 7.0% probability ofissuance during a fifth next period (5NP) due to a receive NOA from athird office action response (e.g., 7.0%×100%=7.0%). The sum of theallowance/issuance probability for the fourth next period is 7.0%. Thereis a 2.3% probability of issuance during a sixth next period (6NP) dueto a receive NOA from a fourth office action response (e.g.,2.3%×100%=2.3%). The sum of the allowance/issuance probability for thesixth next period is 2.3%.

FIG. 228 is a diagram of an example of issuance forecasting timingwindows for a patent application forecasted to receive a first officeaction in the current period. For example, the issuance forecastingtimeline includes a current period, a first next period, a second nextperiod, a third next period, a fourth next period, a fifth next period,and a sixth next period. More or less periods are possible based on thedesired forecasting.

The growth and expense co-processor forecasts when issuances will likelyoccur based on programmable time frames. The programmable time framesmay be based on past performance, industry averages, default settings,and/or details of prosecution (e.g., when office action responses arefiled, etc.). The programmable time frames may be continually updatedbased on newly ingested data.

The forecasting occurs on a per patent application basis or based on anaverage filing date for new applications. In this example, a newapplication (e.g., a second patent application) has a filing date thatoccurs prior to the current period and a first office action isprojected to be received in the current period. If a first office actionallowance occurs, a notice of allowance (NOA) occurs at the beginning ofthe current period. For this example, office action responses areassumed to be filed in the middle of an office action (OA) window. Forexample, a response to first office action is filed toward the end ofthe current period after a time d2 (where σ is the time frame of a firstoffice action window).

A programmable time frame (λ) is the time after filing an office actionto receiving a notice of allowance. The programmable time frame (1.5ε)is the time window between filing office action responses (where a isthe time frame of subsequent office action windows). As shown, afterfiling a first office action response after a period of σ/2, a notice ofallowance may occur after a time frame λ(e.g., about one-quarter intothe first next period).

If a notice of allowance does not occur after a first office action,after a period of 1.5ε from filing a first office action response, aresponse to a second office action is filed. After filing a secondoffice action response, a notice of allowance may occur after a timeframe λ(e.g., about half way into the second next period).

If a notice of allowance does not occur after a second office action,after a period of 1.5ε from filing a second office action response, aresponse to a third office action is filed. After filing a third officeaction response, a notice of allowance may occur after a time frameλ(e.g., about three-quarters into the third next period).

If a notice of allowance does not occur after a third office action,after a period of 1.5ε from filing a third office action response, aresponse to a fourth office action is filed. After filing a fourthoffice action response, a notice of allowance may occur after a timeframe λ(e.g., about one-twelfth into the fifth next period). Theissuance forecasting may be forecasted for longer or shorter than sixnext periods and depends on the technology, the phase of the technology,and the amount of forecasting desired.

FIG. 229 is a diagram of an example of issuance forecasting parametersas determined and used by a growth and expense co-processor of animproved computer for technology based on the timing of FIG. 228 . Theissuance probability is calculated by multiplying issuance actionreceive probability by an allowance probability. Receive and allowanceprobabilities may be based on historical data, a particular market-techunit, default settings, etc.

Issuance actions (similar to prosecution actions as previouslydiscussed) include a first office action (OA) allowance, a receive firstoffice action, a receive second office action, a receive third officeaction, a receive fourth office action, and a receive another officeaction. The receive probability of a first office action allowance is5%, the receive probability of a first office action is 95%, the receiveprobability of a second office action is 31.64%, the receive probabilityof a third office action is 10.53%, the receive probability of a fourthoffice action is 3.51%, and the receive probability of another officeaction is 1.17%.

If a first office action allowance is received, the allowanceprobability is 100%, if a first office action is received the allowanceprobability is 66.7%, if a second office action is received theallowance probability is 66.7%, if a third office action is received theallowance probability is 66.7%, if a fourth office action is receivedthe allowance probability is 66.7%, and if another office action isreceived the allowance probability is 66.7%.

The issuance probability due to a first office action allowance is 5.0%(e.g., 5%×100%). The issuance probability after receiving a first officeaction is 63.4% (e.g., 95%×66.7%). The issuance probability afterreceiving a second office action is 21.1% (e.g., 31.64%×66.7%). Theissuance probability after receiving a third office action is 7.0%(e.g., 10.53%×66.7%). The issuance probability after receiving a fourthoffice action is 2.3% (e.g., 3.51%×66.7%). The issuance probabilityafter receiving a fifth office action is 0.8% (e.g., 1.17%×66.7%).

FIG. 230 is a diagram of an example of issuance forecasting timingwindows for a second patent application that is forecasted to receive afirst office action in the current period. The diagram of FIG. 230 issimilar to the diagram of FIG. 228 except that a respond to a fifthoffice action is shown at the beginning of the sixth period.

In this example, a new application (e.g., a second patent application)has a filing date that occurs prior to the current period and a firstoffice action is projected to be received in the current period. If afirst office action allowance occurs, a notice of allowance (NOA) occursat the beginning of the current period. For this example, office actionresponses are assumed to be filed in the middle of an office action (OA)window. For example, a response to first office action is filed towardthe end of the current period after a time λ/2 (where σ is the timeframe of a first office action window).

A programmable time frame (λ) is the time after filing an office actionto receiving a notice of allowance. The programmable time frame (1.5ε)is the time window between filing office action responses (where a isthe time frame of subsequent office action windows). As shown, afterfiling a first office action response after a period of σ/2, a notice ofallowance may occur after a time frame λ(e.g., about one-quarter intothe first next period).

If a notice of allowance does not occur after a first office action,after a period of 1.5ε from filing a first office action response, aresponse to a second office action is filed. After filing a secondoffice action response, a notice of allowance may occur after a timeframe λ(e.g., about half way into the second next period).

If a notice of allowance does not occur after a second office action,after a period of 1.5ε from filing a second office action response, aresponse to a third office action is filed. After filing a third officeaction response, a notice of allowance may occur after a time frameλ(e.g., about three-quarters into the third next period).

If a notice of allowance does not occur after a third office action,after a period of 1.5ε from filing a third office action response, aresponse to a fourth office action is filed. After filing a fourthoffice action response, a notice of allowance may occur after a timeframe λ(e.g., about one-twelfth into the fifth next period). If a noticeof allowance does not occur after a fourth office action, after a periodof 1.5ε from filing a fourth office action response, a response to afifth office action is filed. After filing a fifth office actionresponse, a notice of allowance may occur after a time frame λ(e.g.,about one-third into the sixth next period).

FIG. 231 is a diagram of an example of forecasted probabilities of whena notice of allowance for the second patent application will be receivedas determined by a growth and expense co-processor of an improvedcomputer for technology. In light of the timing windows discussed withreference to FIG. 230 , timing probabilities for issuance can becalculated for a period. The dates for potential notices of allowance(NOAs) can be calculated and then the period those dates are in aredetermined. For example, with a second patent application is filed priorto a current period (CP) and a first office action is expected to bereceived in the current period, if a NOA is received from a first officeaction allowance, there is a 100% probability of issuance during thecurrent period. If a NOA is received from a first office actionresponse, there is a 100% probability of issuance during a first nextperiod (1NP).

If a NOA is received from a second office action response, there is a100% probability of issuance during a second next period (2NP). If a NOAis received from a third office action response, there is a 100%probability of issuance during the third next period (3NP). If a NOA isreceived from a fourth office action response, there is a 100%probability of issuance during the fifth next period (5NP). If a NOA isreceived from a fifth office action response (e.g., “another” OAresponse), there is a 100% probability of issuance during the sixth nextperiod (6NP).

FIG. 232 is a diagram of an example of forecasted probabilities of whena notice of allowance will be received combined with the forecastedprobabilities of receiving a notice of allowance for the second patentapplication as determined by a growth and expense co-processor of animproved computer for technology. To determine the timing probabilitiesfor issuance, the issuance probabilities based on office action (OA) aremultiplied by the timing probabilities for issuance in a period.

The issuance probabilities based on office action were discussed withreference to FIG. 229 . The issuance probability due to a first officeaction allowance is 5.0%, the issuance probability after receiving afirst office action is 63.4%, the issuance probability after receiving asecond office action is 21.1%. The issuance probability after receivinga third office action is 7.0%. The issuance probability after receivinga fourth office action is 2.3%. The issuance probability after receivinga fifth office action is 0.8%.

The timing probabilities for issuance in a period were discussed withreference to FIG. 231 . With a second patent application filed prior toa current period (CP) and a first office action expected in the currentperiod, if a NOA is received from a first office action allowance, thereis a 100% probability of issuance during the current period. If a NOA isreceived from a first office action response, there is a 100%probability of issuance during the first next period (1NP). If a NOA isreceived from a second office action response, there is a 100%probability of issuance during a second next period (2NP). If a NOA isreceived from a third office action response, there is a 100%probability of issuance during the third next period (3NP). If a NOA isreceived from a fourth office action response, there is a 100%probability of issuance during the fifth next period (5NP). If a NOA isreceived from another office action response, there is a 100%probability of issuance during the sixth next period (6NP).

As such, with a second patent application expecting a first officeaction in a current period (CP), there is a 5% probability of issuanceduring a current period (CP) due to a receive NOA from a first officeaction allowance (e.g., 5%×100%=5%). The sum of the allowance/issuanceprobability for the current period is thus 5%. There is a 63.4%probability of issuance during a first next period (1NP) due to areceive NOA from a first office action response (e.g.,63.4%×100%=63.4%). The sum of the allowance/issuance probability for thecurrent period is thus 63.4%.

There is a 21.1% probability of issuance during a second next period(2NP) due to a receive NOA from a second office action response (e.g.,21.1%×100%=21.1%). The sum of the allowance/issuance probability for thesecond next period is thus 21.1%. There is a 7.0% probability ofissuance during a third next period (3NP) due to a receive NOA from athird office action response (e.g., 7.0%×100%=7.0%). The sum of theallowance/issuance probability for the third next period is thus 7.0%.There is a zero percent probability of issuance in a fourth next period(4NP). There is a 2.3% probability of issuance during a fifth nextperiod (5NP) due to a receive NOA from a fourth office action response(e.g., 2.3%×100%=2.3%). The sum of the allowance/issuance probabilityfor the fifth next period is 2.3%.

There is a 0.8% probability of issuance during a sixth next period (6NP)due to a receive NOA from another office action response (e.g.,0.8%×100%=0.8%). The sum of the allowance/issuance probability for thesixth next period is 0.8%.

FIG. 233 is a diagram of an example of issuance forecasting timingwindows for a patent application forecasted to receive a second officeaction in the first next period. For example, the issuance forecastingtimeline includes a current period, a first next period, a second nextperiod, a third next period, a fourth next period, a fifth next period,and a sixth next period. More or less periods are possible based on thedesired forecasting.

The growth and expense co-processor forecasts when issuances will likelyoccur based on programmable time frames. The programmable time framesmay be based on past performance, industry averages, default settings,and/or details of prosecution (e.g., when office action responses arefiled, etc.). The programmable time frames may be continually updatedbased on newly ingested data.

The forecasting occurs on a per patent application basis or based on anaverage filing date for new applications. In this example, a newapplication (e.g., a third patent application) has a filing date thatoccurs prior to the current period, and a first office action responsewas filed in the current period. For this example, office actionresponses are assumed to be filed in the middle of an office action (OA)window. For example, a response to first office action is filed in themiddle of the current period. After a time (ψ+σ/2) (where σ is the timeframe of a second office action window and ψ is a time from after thefirst office action is filed to the beginning of a second office actionwindow).

A programmable time frame (λ) is the time after filing an office actionto receiving a notice of allowance. The programmable time frame (1.5ε)is the time window between filing office action responses (where a isthe time frame of subsequent office action windows). As shown, afterfiling a first office action response, a notice of allowance may occurafter a time frame λ(e.g., about three-quarters of the way through thecurrent period). If a notice of allowance does not occur after the firstoffice action, a second office action response is filed after a periodof ψ+σ/2 from filing a first office action response. A notice ofallowance may occur after a time frame λ(e.g., at the beginning of thesecond next period) from filing the second office action response.

If a notice of allowance does not occur after a second office action,after a period of 1.5ε from filing a second office action response, aresponse to a third office action is filed. After filing a third officeaction response, a notice of allowance may occur after a time frameλ(e.g., about a third into the third next period).

If a notice of allowance does not occur after a third office action,after a period of 1.5ε from filing a third office action response, aresponse to a fourth office action is filed. After filing a fourthoffice action response, a notice of allowance may occur after a timeframe λ(e.g., about half way into the fourth next period). If a noticeof allowance does not occur after a fourth office action, after a periodof 1.5ε from filing a fourth office action response, a response to afifth office action is filed. After filing a fifth office actionresponse, a notice of allowance may occur after a time frame λ(e.g.,about three-quarters of the way into the fifth next period). Theissuance forecasting may be forecasted for longer or shorter than sixnext periods and depends on the technology, the phase of the technology,and the amount of forecasting desired.

FIG. 234 is a diagram of an example of issuance forecasting parametersas determined and used by a growth and expense co-processor of animproved computer for technology based on the timing of FIG. 233 . Theissuance probability is calculated by multiplying issuance actionreceive probability by an allowance probability. Receive and allowanceprobabilities may be based on historical data, a particular market-techunit, default settings, etc.

Issuance actions (similar to prosecution actions as previouslydiscussed) include a first office action (OA) allowance, a receive firstoffice action, a receive second office action, a receive third officeaction, a receive fourth office action, and a receive another officeaction. For a third patent application, because a first office actionhas been filed, there is no receive probability of a first office actionallowance and a 100% receive probability of a first office action. Thereceive probability of a second office action is 33.3%, the receiveprobability of a third office action is 11.1%, the receive probabilityof a fourth office action is 3.7%, and the receive probability ofanother office action is 1.2%.

If a first office action allowance is received, the allowanceprobability is 100%, if a first office action is received the allowanceprobability is 66.7%, if a second office action is received theallowance probability is 66.7%, if a third office action is received theallowance probability is 66.7%, if a fourth office action is receivedthe allowance probability is 66.7%, and if another office action isreceived the allowance probability is 66.7%.

The issuance probability due to a first office action allowance is 0.0%(e.g., 0%×100%). The issuance probability after receiving a first officeaction is 66.7% (e.g., 100%×66.7%). The issuance probability afterreceiving a second office action is 22.2% (e.g., 33.3%×66.7%). Theissuance probability after receiving a third office action is 7.4%(e.g., 11.1%×66.7%). The issuance probability after receiving a fourthoffice action is 2.5% (e.g., 3.7%×66.7%). The issuance probability afterreceiving a fifth office action is 0.8% (e.g., 1.2%×66.7%).

FIG. 235 is a diagram of an example of issuance forecasting timingwindows for a third patent application that is forecasted to receive asecond office action in the first next period. FIG. 235 is similar tothe diagram of FIG. 233 where a new application (e.g., a third patentapplication) has a filing date that occurs prior to the current period,a first office action response was filed in the current period, and asecond office action is projected to be received in the first nextperiod. For this example, office action responses are assumed to befiled in the middle of an office action (OA) window. For example, aresponse to first office action is filed in the middle of the currentperiod. After a time (ψ+σ/2) (where σ is the time frame of a secondoffice action window and ψ is a time from after the first office actionis filed to the beginning of a second office action window).

A programmable time frame (λ) is the time after filing an office actionto receiving a notice of allowance. The programmable time frame (1.5ε)is the time window between filing office action responses (where a isthe time frame of subsequent office action windows). As shown, afterfiling a second office action response after a period of ψ+σ/2 fromfiling a first office action response, a notice of allowance may occurafter a time frame λ(e.g., at the beginning of the second next period).

If a notice of allowance does not occur after a second office action,after a period of 1.5ε from filing a second office action response, aresponse to a third office action is filed. After filing a third officeaction response, a notice of allowance may occur after a time frameλ(e.g., about a third into the third next period).

If a notice of allowance does not occur after a third office action,after a period of 1.5ε from filing a third office action response, aresponse to a fourth office action is filed. After filing a fourthoffice action response, a notice of allowance may occur after a timeframe λ(e.g., about half way into the fourth next period). If a noticeof allowance does not occur after a fourth office action, after a periodof 1.5ε from filing a fourth office action response, a response to afifth office action is filed. After filing a fifth office actionresponse, a notice of allowance may occur after a time frame λ(e.g.,about three-quarters of the way into the fifth next period).

FIG. 236 is a diagram of an example of forecasted probabilities of whena notice of allowance for the third patent application will be receivedas determined by a growth and expense co-processor of an improvedcomputer for technology. In light of the timing windows discussed withreference to FIG. 235 , timing probabilities for issuance can becalculated for a period. The dates for potential notices of allowance(NOAs) can be calculated and then the period those dates are in aredetermined. For example, when a third patent application is filed priorto a current period (CP) and a response to first office action (OA) isfiled in a current period, there is no probability of a NOA receivedfrom a first office action allowance. If a NOA is received from thefirst office action response, there is a 100% probability of issuanceduring the current period (CP).

If a NOA is received from a second office action response, there is a100% probability of issuance during a first next period (1NP). There isno probability of issuance in a second next period (2NP). If a NOA isreceived from a third office action response, there is a 100%probability of issuance during the third next period (3NP). If a NOA isreceived from a fourth office action response, there is a 100%probability of issuance during the fourth next period (4NP). If a NOA isreceived from a fifth office action response (e.g., “another” OAresponse), there is a 100% probability of issuance during the fifth nextperiod (5NP).

FIG. 237 is a diagram of an example of forecasted probabilities of whena notice of allowance will be received combined with the forecastedprobabilities of receiving a notice of allowance for the third patentapplication as determined by a growth and expense co-processor of animproved computer for technology. To determine the timing probabilitiesfor issuance, the issuance probabilities based on office action (OA) aremultiplied by the timing probabilities for issuance in a period.

The issuance probabilities based on office action were discussed withreference to FIG. 234 . The issuance probability due to a first officeaction allowance is 0%, the issuance probability after receiving a firstoffice action is 66.7%, the issuance probability after receiving asecond office action is 22.2%, the issuance probability after receivinga third office action is 7.4%, the issuance probability after receivinga fourth office action is 2.5%, and the issuance probability afterreceiving another office action is 0.8%.

The timing probabilities for issuance in a period were discussed withreference to FIG. 236 . With a third patent application filed prior to acurrent period (CP) and a first office action response filed in acurrent period (CP), there is a 100% probability of issuance during thecurrent period (CP) if an NOA is received from the first office actionresponse. If a NOA is received from a second office action response,there is a 100% probability of issuance during a first next period(1NP). There is no probability of issuance in a second next period(2NP). If a NOA is received from a third office action response, thereis a 100% probability of issuance during the third next period (3NP). Ifa NOA is received from a fourth office action response, there is a 100%probability of issuance during the fourth next period (4NP). If a NOA isreceived from a fifth office action response (e.g., “another” OAresponse), there is a 100% probability of issuance during the fifth nextperiod (5NP).

As such, with a third patent application filed prior to a current period(CP) and the first office action filed in the current period (CP), thereis a 66.7% probability of issuance during a current period (CP) due to areceive NOA from a first office action response (e.g.,66.7%×100%=66.7%). The sum of the allowance/issuance probability for thecurrent period is thus 66.7%.

There is a 22.2% probability of issuance during a first next period(1NP) due to a receive NOA from a second office action response (e.g.,22.2%×100%=22.2%). The sum of the allowance/issuance probability for thefirst next period is thus 22.2%. There is a 0% probability of issuanceduring a second next period (2NP).

There is a 7.4% probability of issuance during a third next period (3NP)due to a receive NOA from a third office action response (e.g.,7.4%×100%=7.4%). The sum of the allowance/issuance probability for thethird next period is thus 7.4%. There is a 2.5% probability of issuanceduring a fourth next period (4NP) due to a receive NOA from a fourthoffice action response (e.g., 2.5%×100%=2.5%). The sum of theallowance/issuance probability for the fourth next period is 2.5%. Thereis a 0.8% probability of issuance during a fifth next period (5NP) dueto a receive NOA from another office action response (e.g.,0.8%×100%=0.8%). The sum of the allowance/issuance probability for thefifth next period is 0.8%. There is a 0% probability of issuance duringa sixth next period (6NP).

FIG. 238 is a diagram of an example of issuance forecasting timingwindows for a patent application forecasted to be filed in the firstnext period. The issuance forecasting timeline includes a series ofperiods (e.g., years). For example, the issuance forecasting timelineincludes a current period, a first next period, a second next period, athird next period, a fourth next period, a fifth next period, and asixth next period. More or less periods are possible based on thedesired forecasting.

The growth and expense co-processor forecasts when issuances will likelyoccur based on programmable time frames. The programmable time framesmay be based on past performance, industry averages, default settings,and/or details of prosecution (e.g., when office action responses arefiled, etc.). The programmable time frames may be continually updatedbased on newly ingested data.

The forecasting occurs on a per patent application basis or based on anaverage filing date for new applications. In this example, a newapplication (e.g., a fourth application) is filed during the middle of afirst next period. The programmable time frame ((δ) is the amount oftime from filing a new application to receiving a first office action(or first office action allowance). The programmable time frame ((δ)spans to about a third of the way into the third next period. If a firstoffice action allowance occurs, a notice of allowance (NOA) occurs atabout a third of the way into the third next period (after theprogrammable time frame (δ)).

For this example, office action responses are assumed to be filed in themiddle of an office action (OA) window. For example, a response to firstoffice action is filed towards the middle of the third next period aftera time β+σ/2 (where 6 is the time frame of a first office actionwindow).

A programmable time frame (λ) is the time after filing an office actionto receiving a notice of allowance. The programmable time frame (1.5ε)is the time window between filing office action responses (where a isthe time frame of subsequent office action windows). As shown, afterfiling a first office action response after a period of β+σ/2, a noticeof allowance may occur after a time frame λ(e.g., about the end of thethird next period).

If a notice of allowance does not occur after a first office action,after a period of 1.5ε from filing a first office action response, aresponse to a second office action is filed. After filing a secondoffice action response, a notice of allowance may occur after a timeframe λ(e.g., about one-fourth into the fifth next period).

If a notice of allowance does not occur after a second office action,after a period of 1.5ε from filing a second office action response, aresponse to a third office action is filed. After filing a third officeaction response, a notice of allowance may occur after a time frameλ(e.g., about half way into the sixth next period). The issuanceforecasting may be forecasted for longer or shorter than six nextperiods and depends on the technology, the phase of the technology, andthe amount of forecasting desired.

FIG. 239 is a diagram of an example of issuance forecasting parametersas determined and used by a growth and expense co-processor of animproved computer for technology based on the timing of FIG. 238 . Theissuance probability is calculated by multiplying issuance actionreceive probability by an allowance probability. Receive and allowanceprobabilities may be based on historical data, a particular market-techunit, default settings, etc.

Issuance actions (similar to prosecution actions as previouslydiscussed) include a first office action (OA) allowance, a receive firstoffice action, a receive second office action, a receive third officeaction, a receive fourth office action, and a receive another officeaction. The receive probability of a first office action allowance is5%, the receive probability of a first office action is 95%, the receiveprobability of a second office action is 31.64%, the receive probabilityof a third office action is 10.53%, the receive probability of a fourthoffice action is 3.51%, and the receive probability of another officeaction is 1.17%.

If a first office action allowance is received, the allowanceprobability is 100%, if a first office action is received the allowanceprobability is 66.7%, if a second office action is received theallowance probability is 66.7%, if a third office action is received theallowance probability is 66.7%, if a fourth office action is receivedthe allowance probability is 66.7%, and if another office action isreceived the allowance probability is 66.7%.

The issuance probability before receiving a first office action forissuance due to a first office action allowance is 5.0% (e.g., 5%×100%).The issuance probability before receiving a first office action forissuance after receiving a first office action is 63.4% (e.g.,95%×66.7%). The issuance probability before receiving a first officeaction for issuance after receiving a second office action is 21.1%(e.g., 31.64%×66.7%). The issuance probability before receiving a firstoffice action for issuance after receiving a third office action is 7.0%(e.g., 10.53%×66.7%). The issuance probability before receiving a firstoffice action for issuance after receiving a fourth office action is2.3% (e.g., 3.51%×66.7%). The issuance probability before receiving afirst office action for issuance after receiving a fifth office actionis 0.8% (e.g., 1.17%×66.7%).

FIG. 240 is a diagram of an example of issuance forecasting timingwindows for a fourth patent application that is forecasted to be filedin the first next period. The diagram of FIG. 240 is similar to thediagram of FIG. 238 . In this example, a new application (e.g., a fourthapplication) is filed during the middle of a first next period. Theprogrammable time frame ((δ) is the amount of time from filing a newapplication to receiving a first office action (or first office actionallowance). The programmable time frame ((δ) spans to about a third ofthe way into the third next period. If a first office action allowanceoccurs, a notice of allowance (NOA) occurs at about a third of the wayinto the third next period (after the programmable time frame (δ)).

For this example, office action responses are assumed to be filed in themiddle of an office action (OA) window. For example, a response to firstoffice action is filed towards the middle of the third next period aftera time β+σ/2 (where 6 is the time frame of a first office actionwindow).

A programmable time frame (λ) is the time after filing an office actionto receiving a notice of allowance. The programmable time frame (1.5ε)is the time window between filing office action responses (where a isthe time frame of subsequent office action windows). As shown, afterfiling a first office action response after a period of β+σ/2, a noticeof allowance may occur after a time frame λ(e.g., about the end of thethird next period).

If a notice of allowance does not occur after a first office action,after a period of 1.5ε from filing a first office action response, aresponse to a second office action is filed. After filing a secondoffice action response, a notice of allowance may occur after a timeframe λ(e.g., about one-fourth into the fifth next period).

If a notice of allowance does not occur after a second office action,after a period of 1.5ε from filing a second office action response, aresponse to a third office action is filed. After filing a third officeaction response, a notice of allowance may occur after a time frameλ(e.g., about half way into the sixth next period). The issuanceforecasting may be forecasted for longer or shorter than six nextperiods and depends on the technology, the phase of the technology, andthe amount of forecasting desired.

FIG. 241 is a diagram of an example of forecasted probabilities of whena notice of allowance for the fourth patent application will be receivedas determined by a growth and expense co-processor of an improvedcomputer for technology. In light of the timing windows discussed withreference to FIG. 240 , timing probabilities for issuance can becalculated for a period. The dates for potential notices of allowance(NOAs) can be calculated and then the period those dates are in aredetermined. For example, when a fourth patent application is filedduring the middle of a first next period, there is no probability ofissuance in a current period (CP), first next period (1NP), or secondnext period (2NP).

If a NOA is received from a first office action allowance, there is 100%probability of issuance during a third next period (3NP). If a NOA isreceived from a first office action response, there is 100% probabilityof issuance during a third next period (3NP). There is no probability ofissuance during a fourth next period (4NP). If a NOA is received from asecond office action response, there is a 100% probability of issuanceduring a fifth next period (1NP). If a NOA is received from a thirdoffice action response, there is a 100% probability of issuance duringthe sixth next period (6NP).

FIG. 242 is a diagram of an example of forecasted probabilities of whena notice of allowance will be received combined with the forecastedprobabilities of receiving a notice of allowance for the fourth patentapplication as determined by a growth and expense co-processor of animproved computer for technology. To determine the timing probabilitiesfor issuance, the issuance probabilities based on office action (OA) aremultiplied by the timing probabilities for issuance in a period.

The issuance probabilities based on office action were discussed withreference to FIG. 239 . The issuance probability due to a first officeaction allowance is 5.0%. The issuance probability after receiving afirst office action is 63.4%. The issuance probability after receiving asecond office action is 21.1%. The issuance probability after receivinga third office action is 7.0%. The issuance probability after receivinga fourth office action is 2.3%. The issuance probability after receivinganother office action is 0.8%.

The timing probabilities for issuance in a period were discussed withreference to FIG. 241 . When a fourth patent application is filed duringthe middle of a first next period, there is no probability of issuancein a current period (CP), first next period (1NP), or second next period(2NP). If a NOA is received from a first office action allowance, thereis 100% probability of issuance during a third next period (3NP). If aNOA is received from a first office action response, there is 100%probability of issuance during a third next period (3NP). There is noprobability of issuance during a fourth next period (4NP). If a NOA isreceived from a second office action response, there is a 100%probability of issuance during a fifth next period (1NP). If a NOA isreceived from a third office action response, there is a 100%probability of issuance during the sixth next period (6NP).

As such, with the patent fourth application filed during the middle of afirst next period, there is a 0% probability of issuance during acurrent period (CP), a first next period (1NP), or a second next period(2NP). The sum of the allowance/issuance probability for the current,first next, and second next periods are thus 0%.

There is a 5% probability of issuance during a third next period (3NP)due to a receive NOA from first office action allowance (e.g.,5%×100%=5%). There is a 63.4% probability of issuance during a thirdnext period (3NP) due to a receive NOA from first office action response(e.g., 63.4%×100%=63.4%). The sum of the allowance/issuance probabilityfor the third next period is thus 68.4% (e.g., 5%+63.4%=68.4%). There isa 0% probability of issuance during a fourth next period (4NP). The sumof the allowance/issuance probability for the fourth next period is thus0%.

There is a 21.1% probability of issuance during a fifth next period(5NP) due to a receive NOA from a second office action response (e.g.,21.1%×100%=21.1%). The sum of the allowance/issuance probability for thefifth next period is thus 21.1%. There is a 7.0% probability of issuanceduring a sixth next period (6NP) due to a receive NOA from a thirdoffice action response (e.g., 7.0%×100%=7.0%).

FIG. 243 is a diagram of an example of combining issuance forecastingprobabilities and timing for the four example patent applications asdetermined by a growth and expense co-processor of an improved computerfor technology. The sum of issuance probabilities for a first patentapplication (as discussed with reference to FIG. 227 ) are 0% for acurrent period (CP), 0% for a first next period, 68.4% for a second nextperiod (2NP), 0% for a third next period (3NP), 21.2% for a fourth nextperiod (4NP), 7.0% for a fifth next period (5NP), and 2.3% for a sixthnext period (6NP).

The sum of issuance probabilities for a second patent application (asdiscussed with reference to FIG. 232 ) are 5% for a current period (CP),63.4% for a first next period (1NP), 21.2% for a second next period(2NP), 7.0% for a third next period (3NP), 0% for a fourth next period(4NP), 2.3% for a fifth next period (5NP), and 0.8% for a sixth nextperiod (6NP).

The sum of issuance probabilities for a third patent application (asdiscussed with reference to FIG. 237 ) are 66.7% for a for a currentperiod (CP), 22.2% for a first next period, 0% for a second next period(2NP), 7.4% for a third next period (3NP), 2.5% for a fourth next period(4NP), 0.8% for a fifth next period (5NP), and 0% for a sixth nextperiod (6NP).

The sum of issuance probabilities for a fourth patent application (asdiscussed with reference to FIG. 242 ) are 0% for a for a current period(CP), 0% for a first next period, 0% for a second next period (2NP),68.4% for a third next period (3NP), 0% for a fourth next period (4NP),21.1% for a fifth next period (5NP), and 7.0% for a sixth next period(6NP).

Based on the sum of issuance probabilities for each patent application,a cumulative sum of issuance probabilities for patent applications I-4over a current-sixth period can be calculated. For example, theprobability of issuance in the current period (CP) is 71.7% (e.g.,66.7%+5%+0%+0%=71.7%). The probability of issuance in the first nextperiod (1NP) is 154% (e.g., 68.4%+63.4%+22.2%+0%=154%). The probabilityof issuance in the second next period (2NP) is 21.2% (e.g., 0% +21.1%+0% +0%=21.1%).

The probability of issuance in the third next period (3NP) is 82.8%(e.g., 0%+7.0%+7.4%+68.4%=82.8%). The probability of issuance in thefourth next period (4NP) is 23.6% (e.g., 21.1%+0%+2.5%+0%=23.6%). Theprobability of issuance in the fifth next period (5NP) is 31.2% (e.g.,7.0%+2.3%+0.8%+21.1%=31.2%). The probability of issuance in the sixthnext period (6NP) is 10.1% (e.g., 2.3%+0.8%+0%+7.0%=10.1%).

Based off of the cumulative sum of issuance probabilities, an amount ofissuances can be estimated. For example, for a current period, 0.72issuances can be expected, for a first next period, 1.54 issuances canbe expected, for a second next period, 0.21 issuances can be expected,for a third next period, 0.83 issuances can be expected, for a fourthnext period, 0.24 issuances can be expected, for a fifth next period,0.31 issuances can be expected, and for a sixth next period, 0.10issuances can be expected.

FIG. 244 is a diagram of an example of calculating expenses for theissuance forecasting probabilities and timing for the four examplepatent applications as determined by a growth and expense co-processorof an improved computer for technology. Using the amount of estimatedissuances discussed with reference to FIG. 243 and issuance fees,issuance expenses can be estimated. In this example, programmable valuesfor issuance fees include a $700 government fee and a $1500 attorney fee(total of $2200) per issuance. Issuance fees can be programmed based oncurrent government fees, a particular clients, industry averages, etc.

For a current period, the forecasted issuance expense for attorney feesis $1,080 (e.g., 0.72 ×$1500), the forecasted issuance expense forgovernment fees is $504 (e.g., 0.72 ×$700), and the total forecastedissuance expense is $1,584 (e.g., $1,080+$504). For a first next period,the forecasted issuance expense for attorney fees is $2,310 (e.g.,1.54×$1500), the forecasted issuance expense for government fees is$1,078 (e.g., 1.54×$700), and the total forecasted issuance expense is$3,388(e.g., $2,310+$1,078). For a second next period, the forecastedissuance expense for attorney fees is $315 (e.g., 0.21×$1500), theforecasted issuance expense for government fees is $147 (e.g.,0.21×$700), and the total forecasted issuance expense is $462 (e.g.,$315+$147).

For a third next period, the forecasted issuance expense for attorneyfees is $1,245 (e.g., 0.83×$1500), the forecasted issuance expense forgovernment fees is $581 (e.g., 0.83×$700), and the total forecastedissuance expense is $1,826 (e.g., $1,245+$581). For a fourth nextperiod, the forecasted issuance expense for attorney fees is $360 (e.g.,0.24×$1500), the forecasted issuance expense for government fees is $168(e.g., 0.24×$700), and the total forecasted issuance expense is $528(e.g., $360+$168).

For a fifth next period, the forecasted issuance expense for attorneyfees is $465 (e.g., 0.31×$1500), the forecasted issuance expense forgovernment fees is $217 (e.g., 0.31×$700), and the total forecastedissuance expense is $682 (e.g., $465+$217). For a sixth next period, theforecasted issuance expense for attorney fees is $150 (e.g.,0.10×$1500), the forecasted issuance expense for government fees is $70(e.g., 0.10×$700), and the total forecasted issuance expense is $220(e.g., $70+$220).

FIG. 245 is a logic diagram of an example of method for forecastingsubsequent filing probabilities and timing as executed by a growth andexpense co-processor of an improved computer for technology. In thisexample, subsequent filings are forecasted domestically (e.g., in theU.S.), but a similar method can be used for forecasting subsequentforeign filings. Subsequent filings include continuation applications,divisional applications, continuation in part applications, legalplaceholder conversion (LPC) applications, and provisional conversionapplications. For provisional conversions, a set period of time “x” maybe used to determine when the conversion will take place.

The method begins with step 1580 where subsequent filing factors areestablished per period. Subsequent filing factors determine an amount offirst subsequent filings per period, and an amount of second and beyondsubsequent filings per period. The subsequent filing factor refers to aweight used to multiply to percentages of each type of subsequentfiling. For example, the subsequent filing factor for a first (e.g.,primary) subsequent filing, may be a 1.25. As another example, thesubsequent filing factor for a second (e.g., secondary) subsequentfiling, may be a 0.5.

The method continues with step 1582 where a primary subsequent filingratio per period is determined between the various types of subsequentfilings (e.g., continuations, divisionals, continuation-in-part (CIPs),and LPCs). For example, for primary subsequent filings, the amount ofLPCs desired may be higher than the amount of continuations. The primarysubsequent filing ratio may be based on the type of application (e.g.,if it is a bundle application), likelihood of a restriction requirement(e.g., based on past performance and/or industry average), desiredpatent position, budget, etc.

The method continues with step 1584 where a secondary subsequent filingratio per period is determined between the various types of subsequentfilings (e.g., continuations, divisionals, continuation-in-part (CIPs),and LPCs). For example, for secondary subsequent filings, the amount ofcontinuations may be more desired that the amount of LPCs. The secondarysubsequent filing ratio may be based on the type of application (e.g.,if it is a bundle application), likelihood of a restriction requirement(e.g., based on past performance and/or industry average), desiredpatent position, budget, etc.

FIG. 246 is a logic diagram of another example of method for forecastingsubsequent filing probabilities and timing as executed by a growth andexpense co-processor of an improved computer for technology. The methodbegins with step 1590 where whether an application is issuing isdetermined. If the application is not issuing, the method branches backto step 1590 until an application issues.

If the application is issuing, the method continues with step 1592 wherewhether the application is a utility or a legal placeholder conversion(LPC) is determined. When the application is a utility or an LPCapplication, the method continues with step 1596 where a subsequentfiling probability based on the subsequent filing factor and primarysubsequent filing ratio (e.g., as discussed with reference to FIG. 245 )is determined.

When the application is not a utility or an LPC application (e.g., theapplication is a subsequent filing), the method continues with step 1598where a subsequent filing probability based on the subsequent filingfactor and a secondary subsequent filing ratio (e.g., as discussed withreference to FIG. 245 ) is determined.

FIG. 247 is a diagram of an example of primary and secondary subsequentfiling forecasting parameters for a first patent application asdetermined by a growth and expense co-processor of an improved computerfor technology. The primary and secondary subsequent filing forecastingparameters may be set for all patents per period or set for all periods.

In this example, the first patent application is a utility application.The primary filing forecasting parameters include a subsequent filingfactor, a continuation factor, a divisional factor, acontinuation-in-part (CIP) factor, and a legal placeholder conversion(LPC) factor. The continuation, divisional, CIP, and LPC factorsrepresent the primary subsequent filing ratio as discussed withreference to FIG. 245 .

For primary filing forecasting, the subsequent filing factor is set at1.25. The continuation factor is set at 15%, the divisional factor isset at 2.5%, the CIP factor is set at 7.5%, and the LPC factor is set at75%. The primary subsequent filing ratio may be based on the type ofapplication (e.g., if it is a bundle application, there will be an LPCfactor), likelihood of a restriction requirement (e.g., based on pastperformance and/or industry average), desired patent position, budget,etc.

The secondary filing forecasting parameters include a subsequent filingfactor, a continuation factor, a divisional factor, acontinuation-in-part (CIP) factor, and a legal placeholder conversion(LPC) factor. The continuation, divisional, CIP, and LPC factorsrepresent the secondary subsequent filing ratio as discussed withreference to FIG. 245 .

For secondary filing forecasting, the subsequent filing factor is set at0.5. The continuation factor is set at 50%, the divisional factor is setat 5%, the CIP factor is set at 20%, and the LPC factor is set at 25%.The secondary subsequent filing ratio may be based on the type ofapplication, likelihood of a restriction requirement (e.g., based onpast performance and/or industry average), desired patent position,budget, etc.

FIG. 248 is a diagram of an example of forecasted probabilities andtiming of a subsequent filing for a first patent application asdetermined by a growth and expense co-processor of an improved computerfor technology. The sum of allowance probabilities of the first patentapplication over the current-sixth next periods was discussed withreference to FIG. 227 .

With the first patent application filed in a current period (CP), thereis zero percent probability of issuance in the current period or thefirst next period (1NP), a 68.4% probability of issuance in the secondnext period (2NP), a zero percent probability of issuance in the thirdnext period (3NP), a 21.1% probability of issuance during a fourth nextperiod (4NP), a 7.0% probability of issuance during a fifth next period(5NP), and a 2.3% probability of issuance during a sixth next period(6NP).

The probability of filing a subsequent filing per period is determinedby multiplying the issuance probability by the probability of a type ofsubsequent filing. The probability of the type of subsequent filing isdetermined by multiplying the subsequent filing factor by the filingtype factor. For example, the probability of a continuation is 18.8%(e.g., 1.25 ×15%=18.8%), the probability of a divisional is 3.1% (e.g.,1.25 ×2.5%=3.1%), the probability of a CIP is 9.4% (e.g., 1.25×7.5%=9.4%), and the probability of an LPC is 93.8% (e.g., 1.25×75%=93.8%)

For the current period (CP) and the first next period (1NP), there is noprobability of a subsequent filing. For a second next period (2NP),there is a 12.9% probability of filing a continuation (e.g.,18.8%×68.4%), a 2.1% probability of filing a divisional (e.g.,3.1%×68.4%), a 6.4% probability of filing a CIP (e.g., 9.4%×68.4%), anda 64.2% probability of filing an LPC (e.g., 93.8%×68.4%).

For a third next period (3NP), there is a 0% probability of a subsequentfiling. For a fourth next period (4NP), there is a 4.0% probability offiling a continuation (e.g., 18.8%×21.1%), a 0.7% probability of filinga divisional (e.g., 3.1%×21.1%), a 2.0% probability of filing a CIP(e.g., 9.4%×21.1%), and a 19.8% probability of filing an LPC (e.g.,93.8%×21.1%). For a fifth next period (5NP), there is a 1.3% probabilityof filing a continuation (e.g., 18.8%×7.0%), a 0.2% probability offiling a divisional (e.g., 3.1%×7.0%), a 0.7% probability of filing aCIP (e.g., 9.4%×7.0%), and a 6.6% probability of filing an LPC (e.g.,93.8%×7.0%). For a sixth next period (6NP), there is a 0.4% probabilityof filing a continuation (e.g., 18.8%×2.3%), a 0.0% probability offiling a divisional (e.g., 3.1%×2.3%), a 0.2% probability of filing aCIP (e.g., 9.4%×2.3%), and a 2.2% probability of filing an LPC (e.g.,93.8%×2.3%).

FIG. 249 is a diagram of an example of primary and secondary subsequentfiling forecasting parameters for a second patent application asdetermined by a growth and expense co-processor of an improved computerfor technology. The primary and secondary subsequent filing forecastingparameters may be set for all patents per period or set for all periods.

In this example, the second patent application is a utility application.The primary filing forecasting parameters include a subsequent filingfactor, a continuation factor, a divisional factor, acontinuation-in-part (CIP) factor, and a legal placeholder conversion(LPC) factor. The continuation, divisional, CIP, and LPC factorsrepresent the primary subsequent filing ratio as discussed withreference to FIG. 245 .

For primary filing forecasting, the subsequent filing factor is set at1.25. The continuation factor is set at 15%, the divisional factor isset at 2.5%, the CIP factor is set at 7.5%, and the LPC factor is set at75%. The primary subsequent filing ratio may be based on the type ofapplication (e.g., if it is a bundle application, there will be an LPCfactor), likelihood of a restriction requirement (e.g., based on pastperformance and/or industry average), desired patent position, budget,etc.

The secondary filing forecasting parameters include a subsequent filingfactor, a continuation factor, a divisional factor, acontinuation-in-part (CIP) factor, and a legal placeholder conversion(LPC) factor. The continuation, divisional, CIP, and LPC factorsrepresent the secondary subsequent filing ratio as discussed withreference to FIG. 245 .

For secondary filing forecasting, the subsequent filing factor is set at0.5. The continuation factor is set at 50%, the divisional factor is setat 5%, the CIP factor is set at 20%, and the LPC factor is set at 25%.The secondary subsequent filing ratio may be based on the type ofapplication, likelihood of a restriction requirement (e.g., based onpast performance and/or industry average), desired patent position,budget, etc.

FIG. 250 is a diagram of an example of forecasted probabilities andtiming of a subsequent filing for a second patent application asdetermined by a growth and expense co-processor of an improved computerfor technology. The sum of allowance probabilities of the second patentapplication over the current-sixth next periods was discussed withreference to FIG. 232 .

With a second patent application expecting a first office action in acurrent period (CP), there is a 5% probability of issuance during acurrent period (CP), a 63.4% probability of issuance during a first nextperiod (1NP), a 21.1% probability of issuance during a second nextperiod (2NP), a 7.0% probability of issuance during a third next period(3NP), a zero percent probability of issuance in a fourth next period(4NP), a 2.3% probability of issuance during a fifth next period (5NP),and a 0.8% probability of issuance during a sixth next period (6NP).

The probability of filing a subsequent filing per period is determinedby multiplying the issuance probability by the probability of a type ofsubsequent filing. The probability of the type of subsequent filing isdetermined by multiplying the subsequent filing factor by the filingtype factor. For example, the probability of a continuation is 18.8%(e.g., 1.25 ×15%=18.8%), the probability of a divisional is 3.1% (e.g.,1.25 ×2.5%=3.1%), the probability of a CIP is 9.4% (e.g., 1.25×7.5%=9.4%), and the probability of an LPC is 93.8% (e.g., 1.25×75%=93.8%)

For the current period (CP) there is a 0.9% probability of filing acontinuation (e.g., 18.8%×5%), a 0.1% probability of filing a divisional(e.g., 3.1%×5%), a 0.5% probability of filing a CIP (e.g., 9.4%×5%), anda 4.7% probability of filing an LPC (e.g., 93.8%×5%). For the first nextperiod (1NP), there is a 11.9% probability of filing a continuation(e.g., 18.8%×63.4%), a 2.0% probability of filing a divisional (e.g.,3.1%×63.4%), a 5.9% probability of filing a CIP (e.g., 9.4%×63.4%), anda 59.5% probability of filing an LPC (e.g., 93.8%×63.4%).

For a second next period (2NP), there is a 4.0% probability of filing acontinuation (e.g., 18.8%×21.1%), a 0.7% probability of filing adivisional (e.g., 3.1%×21.1%), a 2.0% probability of filing a CIP (e.g.,9.4%×21.1%), and a 19.8% probability of filing an LPC (e.g.,93.8%×21.1%).

For a third next period (3NP), there is a 1.3% probability of filing acontinuation (e.g., 18.8%×7.0%), a 0.2% probability of filing adivisional (e.g., 3.1%×7.0%), a 0.7% probability of filing a CIP (e.g.,9.4%×7.0%), and a 6.6% probability of filing an LPC (e.g., 93.8%×7.0%).For a fourth next period (4NP), there is no probability of a subsequentfiling.

For a fifth next period (5NP), there is a 0.4% probability of filing acontinuation (e.g., 18.8%×2.3%), a 0.0% probability of filing adivisional (e.g., 3.1%×2.3%), a 0.2% probability of filing a CIP (e.g.,9.4%×2.3%), and a 2.2% probability of filing an LPC (e.g., 93.8%×2.3%).

For a sixth next period (6NP), there is a 0.0% probability of filing acontinuation (e.g., 18.8%×0.8%), a 0.0% probability of filing adivisional (e.g., 3.1%×0.8%), a 0.0% probability of filing a CIP (e.g.,9.4%×0.8%), and a 0.75% probability of filing an LPC (e.g., 93.8%×0.8%).

FIG. 251 is a diagram of an example of primary and secondary subsequentfiling forecasting parameters for a third patent application asdetermined by a growth and expense co-processor of an improved computerfor technology. The primary and secondary subsequent filing forecastingparameters may be set for all patents per period or set for all periods.

In this example, the third patent application is a utility application.The primary filing forecasting parameters include a subsequent filingfactor, a continuation factor, a divisional factor, acontinuation-in-part (CIP) factor, and a legal placeholder conversion(LPC) factor. The continuation, divisional, CIP, and LPC factorsrepresent the primary subsequent filing ratio as discussed withreference to FIG. 245 .

For primary filing forecasting, the subsequent filing factor is set at1.25. The continuation factor is set at 15%, the divisional factor isset at 2.5%, the CIP factor is set at 7.5%, and the LPC factor is set at75%. The primary subsequent filing ratio may be based on the type ofapplication (e.g., if it is a bundle application, there will be an LPCfactor), likelihood of a restriction requirement (e.g., based on pastperformance and/or industry average), desired patent position, budget,etc.

The secondary filing forecasting parameters include a subsequent filingfactor, a continuation factor, a divisional factor, acontinuation-in-part (CIP) factor, and a legal placeholder conversion(LPC) factor. The continuation, divisional, CIP, and LPC factorsrepresent the secondary subsequent filing ratio as discussed withreference to FIG. 245 .

For secondary filing forecasting, the subsequent filing factor is set at0.5. The continuation factor is set at 50%, the divisional factor is setat 5%, the CIP factor is set at 20%, and the LPC factor is set at 25%.The secondary subsequent filing ratio may be based on the type ofapplication, likelihood of a restriction requirement (e.g., based onpast performance and/or industry average), desired patent position,budget, etc.

FIG. 252 is a diagram of an example of forecasted probabilities andtiming of a subsequent filing for a third patent application asdetermined by a growth and expense co-processor of an improved computerfor technology. The sum of allowance probabilities of the third patentapplication over the current-sixth next periods was discussed withreference to FIG. 237 .

With the third patent application filed prior to a current period (CP)and a first office action response filed in a current period, there is a66.7% probability of issuance during a current period (CP), a 22.2%probability of issuance during a first next period (1NP), a 7.4%probability of issuance during a third next period (3NP), a 2.5%probability of issuance during a fourth next period (4NP), a 0.8%probability of issuance during a fifth next period (5NP), and there is a0% probability of issuance during a sixth next period (6NP).

The probability of filing a subsequent filing per period is determinedby multiplying the issuance probability by the probability of a type ofsubsequent filing. The probability of the type of subsequent filing isdetermined by multiplying the subsequent filing factor by the filingtype factor. For example, the probability of a continuation is 18.8%(e.g., 1.25 ×15%=18.8%), the probability of a divisional is 3.1% (e.g.,1.25 ×2.5%=3.1%), the probability of a CIP is 9.4% (e.g., 1.25×7.5%=9.4%), and the probability of an LPC is 93.8% (e.g., 1.25×75%=93.8%)

For the current period (CP) there is a 12.5% probability of filing acontinuation (e.g., 18.8%×66.7%), a 2.1% probability of filing adivisional (e.g., 3.1%×66.7%), a 6.3% probability of filing a CIP (e.g.,9.4%×66.7%), and a 62.6% probability of filing an LPC (e.g.,93.8%×66.7%).

For the first next period (1NP), there is a 4.2% probability of filing acontinuation (e.g., 18.8%×22.2%), a 0.7% probability of filing adivisional (e.g., 3.1%×22.2%), a 2.1% probability of filing a CIP (e.g.,9.4%×22.2%), and a 20.8% probability of filing an LPC (e.g.,93.8%×22.2%). For the second next period (2NP) there is a 0% probabilityof subsequent filings.

For a third next period (3NP), there is a 1.4% probability of filing acontinuation (e.g., 18.8%×7.4%), a 0.2% probability of filing adivisional (e.g., 3.1%×7.4%), a 0.7% probability of filing a CIP (e.g.,9.4%×7.4%), and a 6.9% probability of filing an LPC (e.g., 93.8%×7.4%).

For a fourth next period (4NP), there is a 0.5% probability of filing acontinuation (e.g., 18.8%×2.5%), a 0% probability of filing a divisional(e.g., 3.1%×2.5%), a 0.2% probability of filing a CIP (e.g., 9.4%×2.5%),and a 2.3% probability of filing an LPC (e.g., 93.8%×2.5%).

For a fifth next period (5NP), there is a 0.2% probability of filing acontinuation (e.g., 18.8%×0.8%), a 0% probability of filing a divisional(e.g., 3.1%×0.8%), a 0% probability of filing a CIP (e.g., 9.4%×0.8%),and a 0.75% probability of filing an LPC (e.g., 93.8%×0.8%). For a sixthnext period (6NP), there is a 0% probability of subsequent filings.

FIG. 253 is a diagram of an example of primary and secondary subsequentfiling forecasting parameters for a fourth patent application asdetermined by a growth and expense co-processor of an improved computerfor technology. The primary and secondary subsequent filing forecastingparameters may be set for all patents per period or set for all periods.

In this example, the third patent application is a utility application.The primary filing forecasting parameters include a subsequent filingfactor, a continuation factor, a divisional factor, acontinuation-in-part (CIP) factor, and a legal placeholder conversion(LPC) factor. The continuation, divisional, CIP, and LPC factorsrepresent the primary subsequent filing ratio as discussed withreference to FIG. 245 .

For primary filing forecasting, the subsequent filing factor is set at1.25. The continuation factor is set at 15%, the divisional factor isset at 2.5%, the CIP factor is set at 7.5%, and the LPC factor is set at75%. The primary subsequent filing ratio may be based on the type ofapplication (e.g., if it is a bundle application, there will be an LPCfactor), likelihood of a restriction requirement (e.g., based on pastperformance and/or industry average), desired patent position, budget,etc.

The secondary filing forecasting parameters include a subsequent filingfactor, a continuation factor, a divisional factor, acontinuation-in-part (CIP) factor, and a legal placeholder conversion(LPC) factor. The continuation, divisional, CIP, and LPC factorsrepresent the secondary subsequent filing ratio as discussed withreference to FIG. 245 .

For secondary filing forecasting, the subsequent filing factor is set at0.5. The continuation factor is set at 50%, the divisional factor is setat 5%, the CIP factor is set at 20%, and the LPC factor is set at 25%.The secondary subsequent filing ratio may be based on the type ofapplication, likelihood of a restriction requirement (e.g., based onpast performance and/or industry average), desired patent position,budget, etc.

FIG. 254 is a diagram of an example of forecasted probabilities andtiming of a subsequent filing for a fourth patent application asdetermined by a growth and expense co-processor of an improved computerfor technology. The sum of allowance probabilities of the fourth patentapplication over the current-sixth next periods was discussed withreference to FIG. 242 .

With the fourth patent application filed during the middle of a firstnext period, there is a 0% probability of issuance during a currentperiod (CP), a first next period (1NP), or a second next period (2NP).There is a 68.4% probability of issuance during a third next period(3NP), a 0% probability of issuance during a fourth next period (4NP), a21.1% probability of issuance during a fifth next period (5NP), and a7.0% probability of issuance during a sixth next period (6NP).

The probability of filing a subsequent filing per period is determinedby multiplying the issuance probability by the probability of a type ofsubsequent filing. The probability of the type of subsequent filing isdetermined by multiplying the subsequent filing factor by the filingtype factor. Here, the secondary subsequent filing factors are used. Forexample, the probability of a continuation is 25% (e.g., 0.5 ×50%=25%),the probability of a divisional is 2.5% (e.g., 0.5 ×5%=2.5%), theprobability of a CIP is 10.0% (e.g., 0.5 ×20%=10%), and the probabilityof an LPC is 12.5% (e.g., 0.5 ×25%=12.5%)

For the current period (CP), the first next period (1NP), and the secondnext period (2NP) there is a 0% probability of subsequent filings. Forthe third next period (1NP), there is a 17.1% probability of filing acontinuation (e.g., 25%×68.4%), a 1.7% probability of filing adivisional (e.g., 2.5%×68.4%), a 6.8% probability of filing a CIP (e.g.,10.0%×68.4%), and a 8.6% probability of filing an LPC (e.g.,12.5%×68.4%). For the fourth next period (4NP) there is a 0% probabilityof subsequent filings.

For the fifth next period (5NP), there is a 5.3% probability of filing acontinuation (e.g., 25%×21.1%), a 0.5% probability of filing adivisional (e.g., 2.5%×21.1%), a 2.1% probability of filing a CIP (e.g.,10.0%×21.1%), and a 2.6% probability of filing an LPC (e.g.,12.5%×21.1%). For a sixth next period (6NP), there is a 1.75%probability of filing a continuation (e.g., 25%×7.0%), a 0.2%probability of filing a divisional (e.g., 2.5%×7.0%), a 0.7% probabilityof filing a CIP (e.g., 10.0%×7.0%), and a 0.9% probability of filing anLPC (e.g., 12.5%×7.0%).

FIG. 255 is a diagram of an example of forecasted probabilities andtiming of a filing continuation (CON) patent application for each of thefour patent applications as determined by a growth and expenseco-processor of an improved computer for technology.

For a first patent application (as discussed with reference to FIG. 248), there is a 12.9% probability of filing a continuation in the secondnext period (2NP), a 4.0% probability of filing a continuation in fourthnext period (4NP), a 1.3% probability of filing a continuation in fifthnext period (5NP), and a 0.4% probability of filing a continuation insixth next period (6NP).

For a second patent application (as discussed with reference to FIG. 250), there is a 0.9% probability of filing a continuation in the currentperiod (CP), there is a 11.9% probability of filing a continuation inthe first next period (1NP), there is a 4.0% probability of filing acontinuation in the second next period (2NP), there is a 1.3%probability of filing a continuation in the third next period (3NP),there is a 0.4% probability of filing a continuation in the fifth nextperiod (5NP), and there is a 0.0% probability of filing a continuationin the sixth next period (6NP).

For a third patent application (as discussed with reference to FIG. 252), there is a 12.5% probability of filing a continuation in the currentperiod (CP), there is a 4.2% probability of filing a continuation in thefirst next period (1NP), there is a 1.4% probability of filing acontinuation in the third next period (3NP), there is a 0.5% probabilityof filing a continuation in the fourth next period (4NP), and there is a0.2% probability of filing a continuation in the fifth next period(5NP).

For a fourth patent application (as discussed with reference to FIG. 254), there is a 17.1% probability of filing a continuation in the thirdnext period (3NP), there is a 5.3% probability of filing a continuationin the fifth next period (5NP), and there is a 1.75% probability offiling a continuation in the sixth next period (6NP).

The sum of the continuation filing probabilities for the current periodis 13.4% (e.g., 12.5%+0.9%+0%+0%). The sum of the continuation filingprobabilities for the first next period (1NP) is 16.1% (e.g.,0%+11.9%+4.2%+0%). The sum of the continuation filing probabilities forthe second next period (2NP) is 16.9% (e.g., 12.0%+4.0%+0%+0%). The sumof the continuation filing probabilities for the third next period (3NP)is 19.8% (e.g., 0%+1.3%+1.4%+17.1%). The sum of the continuation filingprobabilities for the fourth next period (4NP) is 4.5% (e.g.,4.0%+0%+0.5%+0%). The sum of the continuation filing probabilities forthe fifth next period (5NP) is 7.2% (e.g., 1.3%+0.4%+0.2%+5.3%). The sumof the continuation filing probabilities for the sixth next period (6NP)is 2.15% (e.g., 0.4%+0%+0%+1.75%).

From the sums of continuation filing probabilities, the growth andexpense co-processor is operable to estimate the number of continuationfilings per period. In the current period (CP) there will be 0.13continuations filed based on the 13.4% filing probability. In the firstnext period (1NP) there will be 0.16 continuations filed based on the16.1% filing probability. In the second next period (2NP) there will be0.17 continuations filed based on the 16.9% filing probability. In thethird next period (3NP) there will be 0.20 continuations filed based onthe 19.8% filing probability. In the fourth next period (4NP) there willbe 0.05 continuations filed based on the 4.5% filing probability. In thefifth next period (5NP) there will be 0.07 continuations filed based onthe 7.2% filing probability. In the sixth next period (6NP) there willbe 0.02 continuations filed based on the 2.15% filing probability.

FIG. 256 is a diagram of an example of forecasted probabilities andtiming of a filing divisional (DIV) patent application for each of thefour patent applications as determined by a growth and expenseco-processor of an improved computer for technology.

For a first patent application (as discussed with reference to FIG. 248), there is a 2.1% probability of filing a divisional in the second nextperiod (2NP), a 0.7% probability of filing a divisional in fourth nextperiod (4NP), a 0.2% probability of filing a divisional in fifth nextperiod (5NP), and a 0.0% probability of filing a divisional in sixthnext period (6NP).

For a second patent application (as discussed with reference to FIG. 250), there is a 0.1% probability of filing a divisional in the currentperiod (CP), there is a 2.0% probability of filing a divisional in thefirst next period (1NP), there is a 0.7% probability of filing adivisional in the second next period (2NP), there is a 0.2% probabilityof filing a divisional in the third next period (3NP), there is a 0.0%probability of filing a divisional in the fifth next period (5NP), andthere is a 0.0% probability of filing a divisional in the sixth nextperiod (6NP).

For a third patent application (as discussed with reference to FIG. 252), there is a 2.1% probability of filing a divisional in the currentperiod, there is a 0.7% probability of filing a divisional in the firstnext period (1NP), there is a 0.2% probability of filing a divisional inthe third next period (3NP), there is a 0% probability of filing adivisional in the fifth next period (5NP), and there is a 0% probabilityof filing a divisional in the sixth next period (6NP).

For a fourth patent application (as discussed with reference to FIG. 254), there is a 1.7% probability of filing a divisional in the third nextperiod (3NP), there is a 0.5% probability of filing a divisional in thefifth next period (5NP), and there is a 0.2% probability of filing adivisional in the sixth next period (6NP).

The sum of the divisional filing probabilities for the current period is2.2% (e.g., 0%+0.1%+2.1%+0%). The sum of the divisional filingprobabilities for the first next period (1NP) is 2.7% (e.g.,0%+2.0%+0.7%+0%). The sum of the divisional filing probabilities for thesecond next period (2NP) is 2.8% (e.g., 2.1%+0.7%+0%+0%). The sum of thedivisional filing probabilities for the third next period (3NP) is 2.1%(e.g., 0%+0.2%+0.2%+1.7%). The sum of the divisional filingprobabilities for the fourth next period (4NP) is 0.7% (e.g.,0.7%+0%+0%+0%). The sum of the divisional filing probabilities for thefifth next period (5NP) is 0.7% (e.g., 0.2%+0%+0%+0.5%). The sum of thedivisional filing probabilities for the sixth next period (6NP) is 0.2%(e.g., 0%+0%+0%+0.2%).

From the sums of divisional filing probabilities, the growth and expenseco-processor is operable to estimate the number of divisional filingsper period. In the current period (CP) there will be 0.02 divisionalapplications filed based on the 2.2% filing probability. In the firstnext period (1NP) there will be 0.03 divisional applications filed basedon the 2.7% filing probability. In the second next period (2NP) therewill be 0.03 divisional applications filed based on the 2.8% filingprobability. In the third next period (3NP) there will be 0.02divisional applications filed based on the 2.1% filing probability. Inthe fourth next period (4NP) there will be 0 divisional applicationsfiled based on the 0.7% filing probability. In the fifth next period(5NP) there will be 0 divisional applications filed based on the 0.7%filing probability. In the sixth next period (6NP) there will be 0divisional applications filed based on the 0.2% filing probability.

FIG. 257 is a diagram of an example of forecasted probabilities andtiming of a filing continuation-in-part (CIP) patent application foreach of the four patent applications as determined by a growth andexpense co-processor of an improved computer for technology.

For a first patent application (as discussed with reference to FIG. 248), there is a 6.4% probability of filing a CIP in the second next period(2NP), a 2.0% probability of filing a CIP in fourth next period (4NP), a0.7% probability of filing a CIP in fifth next period (5NP), and a 0.2%probability of filing a CIP in sixth next period (6NP).

For a second patent application (as discussed with reference to FIG. 250), there is a 0.5% probability of filing a CIP in the current period(CP), there is a 5.9% probability of filing a CIP in the first nextperiod (1NP), there is a 2.0% probability of filing a CIP in the secondnext period (2NP), there is a 0.7% probability of filing a CIP in thethird next period (3NP), there is a 0.2% probability of filing a CIP inthe fifth next period (5NP), and there is a 0% probability of filing aCIP in the sixth next period (6NP).

For a third patent application (as discussed with reference to FIG. 252), there is a 6.3% probability of filing a CIP in the current period(CP), there is a 2.1% probability of filing a CIP in the first nextperiod (1NP), there is a 0.7% probability of filing a CIP in the thirdnext period (3NP), there is a 0.2% probability of filing a CIP in thefifth next period (5NP), and a 0% probability of filing a CIP in thesixth next period (6NP).

For a fourth patent application (as discussed with reference to FIG. 254), there is a 6.8% probability of filing a CIP in the third next period(3NP), there is a 2.1% probability of filing a CIP in the fifth nextperiod (5NP), and there is a 0.7% probability of filing a CIP in thesixth next period (6NP).

The sum of the CIP filing probabilities for the current period is 6.8%(e.g., 0%+0.5%+6.3%+0%). The sum of the CIP filing probabilities for thefirst next period (1NP) is 8.0% (e.g., 0%+5.9%+2.1%+0%). The sum of theCIP filing probabilities for the second next period (2NP) is 8.4% (e.g.,6.4%+2.0%+0%+0%). The sum of the CIP filing probabilities for the thirdnext period (3NP) is 8.2% (e.g., 0%+0.7%+0.7%+6.8%). The sum of the CIPfiling probabilities for the fourth next period (4NP) is 2.2% (e.g.,2.0%+0%+0.2%+0%). The sum of the CIP filing probabilities for the fifthnext period (5NP) is 3.0% (e.g., 0.7%+0.2%+0%+2.1%). The sum of the CIPfiling probabilities for the sixth next period (6NP) is 0.9% (e.g., 0.2%+0% +0%+0.7%).

From the sums of CIP filing probabilities, the growth and expenseco-processor is operable to estimate the number of CIP filings perperiod. In the current period (CP) there will be 0.07 CIP applicationsfiled based on the 6.8% filing probability. In the first next period(1NP) there will be 0.08 CIP applications filed based on the 8.0% filingprobability. In the second next period (2NP) there will be 0.08 CIPapplications filed based on the 8.4% filing probability. In the thirdnext period (3NP) there will be 0.08 CIP applications filed based on the8.2% filing probability. In the fourth next period (4NP) there will be0.02 CIP applications filed based on the 2.2% filing probability. In thefifth next period (5NP) there will be 0.03 CIP applications filed basedon the 3.0% filing probability. In the sixth next period (6NP) therewill be 0 CIP applications filed based on the 0.9% filing probability.

FIG. 258 is a diagram of an example of forecasted probabilities andtiming of a filing legal placeholder conversion (LPC) patent applicationfor each of the four patent applications as determined by a growth andexpense co-processor of an improved computer for technology. For a firstpatent application (as discussed with reference to FIG. 248 ), there isa 64.2% probability of filing a LPC in the second next period (2NP), a19.8% probability of filing a LPC in fourth next period (4NP), a 6.6%probability of filing a LPC in fifth next period (5NP), and a 2.2%probability of filing a LPC in sixth next period (6NP).

For a second patent application (as discussed with reference to FIG. 250), there is a 4.7% probability of filing a LPC in the current period(CP), there is a 59.5% probability of filing a LPC in the first nextperiod (1NP), there is a 19.8% probability of filing a LPC in the secondnext period (2NP), there is a 6.6% probability of filing a LPC in thethird next period (3NP), there is a 2.2% probability of filing a LPC inthe fifth next period (5NP), and there is a 0.75% probability of filinga LPC in the sixth next period (6NP).

For a third patent application (as discussed with reference to FIG. 252), there is a 62.6% probability of filing a LPC in the current period(CP), there is a 20.8% probability of filing a LPC in the first nextperiod (1NP), there is a 6.9% probability of filing a LPC in the thirdnext period (3NP), there is a 2.3% probability of filing a LPC in thefourth next period (4NP), and there is a 0.75% probability of filing aLPC in the fifth next period (5NP).

For a fourth patent application (as discussed with reference to FIG. 254), there is a 8.6% probability of filing a LPC in the third next period(3NP), there is a 2.6% probability of filing a LPC in the fifth nextperiod (5NP), and there is a 0.9% probability of filing a LPC in thesixth next period (6NP).

The sum of the LPC filing probabilities for the current period is 67.3%(e.g., 0%+4.7%+62.6%+0%). The sum of the LPC filing probabilities forthe first next period (1NP) is 80.3% (e.g., 0%+59.5%+20.8%+0%). The sumof the LPC filing probabilities for the second next period (2NP) is 84%(e.g., 64.2%+19.8%+0%+0%). The sum of the LPC filing probabilities forthe third next period (3NP) is 22.1% (e.g., 0%+6.6%+6.9%+8.6%). The sumof the LPC filing probabilities for the fourth next period (4NP) is22.1% (e.g., 19.8%+0%+2.3%+0%). The sum of the LPC filing probabilitiesfor the fifth next period (5NP) is 12.2% (e.g., 6.6%+2.2%+0.75%+2.6%).The sum of the LPC filing probabilities for the sixth next period (6NP)is 3.9% (e.g., 2.2%+0.75%+0%+0.9%).

From the sums of LPC filing probabilities, the growth and expenseco-processor is operable to estimate the number of LPC filings perperiod. In the current period (CP) there will be 0.67 LPC applicationsfiled based on the 67.3% filing probability. In the first next period(1NP) there will be 0.8 LPC applications filed based on the 80.3% filingprobability. In the second next period (2NP) there will be 0.84 LPCapplications filed based on the 84% filing probability. In the thirdnext period (3NP) there will be 0.22 LPC applications filed based on the22.1% filing probability. In the fourth next period (4NP) there will be0.22 LPC applications filed based on the 22.1% filing probability. Inthe fifth next period (5NP) there will be 0.12 LPC applications filedbased on the 12.2% filing probability. In the sixth next period (6NP)there will be 0.04 LPC applications filed based on the 3.9% filingprobability.

FIG. 259 is a diagram of an example of forecasted probabilities andtiming of receiving office actions, receiving notices of allowance, andof filing subsequent patent applications relating to an MTU asdetermined by a growth and expense co-processor of an improved computerfor technology.

Based on the prosecution forecasting discussed for the four patentapplications with reference to at least FIG. 221 , there are 0.05 firstoffice action (OA) allowance responses expected during a current period(CP), zero first office action allowance responses expected during afirst next period (1NP), 0.05 first office action allowance responsesexpected during a second next period (2NP), 0.045 first office actionallowance responses expected during a third next period (3NP), 0.005first office action allowance responses expected during a fourth nextperiod (4NP), zero first office action allowance responses expectedduring a fifth next period (5NP), and zero first office action allowanceresponses expected during a sixth next period (6NP).

Further, there are 0.95 full office action (OA) responses expectedduring a current period (CP), 0.52 full office action responses expectedduring a first next period (1NP), 1.19 full office action responsesexpected during a second next period (2NP), 1.23 full office actionresponses expected during a third next period (3NP), 0.44 full officeaction responses expected during a fourth next period (4NP), 0.25 fulloffice action responses expected during a fifth next period (5NP), and0.13 full office action responses expected during a sixth next period(6NP).

Therefore, there is one total office action response expected during acurrent period (CP), 0.52 total office action responses expected duringa first next period (1NP), 1.24 total office action responses expectedduring a second next period (2NP), 1.27 total office action responsesexpected during a third next period (3NP), 0.45 total office actionresponses expected during a fourth next period (4NP), 0.25 total officeaction responses expected during a fifth next period (5NP), and 0.13total office action responses expected during a sixth next period (6NP).

Based on the issuance forecasting discussed for the four patentapplications with reference to at least FIG. 242 , there are 0.72issuances expected during a current period (CP), 1.54 issuances expectedduring a first next period (1NP), 0.21 issuances expected during asecond next period (2NP), 0.83 issuances expected during a third nextperiod (3NP), 0.24 issuances expected during a fourth next period (4NP),0.31 issuances expected during a fifth next period (5NP), and 0.10issuances expected during a sixth next period (6NP).

Based on the subsequent filing forecasting discussed for the four patentapplications with reference to at least FIGS. 255-258 , there are 0.13continuation filings expected during a current period (CP), 0.16continuation filings expected during a first next period (1NP), 0.17continuation filings expected during a second next period (2NP), 0.20continuation filings expected during a third next period (3NP), 0.05continuation filings expected during a fourth next period (4NP), 0.07continuation filings expected during a fifth next period (5NP), and 0.02continuation filings expected during a sixth next period (6NP).

There are 0.02 divisional filings expected during a current period (CP),0.03 divisional filings expected during a first next period (1NP), 0.03divisional filings expected during a second next period (2NP), 0.03divisional filings expected during a third next period (3NP), zerodivisional filings expected during a fourth next period (4NP), zerodivisional filings expected during a fifth next period (5NP), and zerodivisional filings expected during a sixth next period (6NP).

There are 0.07 continuation-in-part (CIP) filings expected during acurrent period (CP), 0.08 CIP filings expected during a first nextperiod (1NP), 0.08 CIP filings expected during a second next period(2NP), 0.08 CIP filings expected during a third next period (3NP), 0.02CIP filings expected during a fourth next period (4NP), 0.03 CIP filingsexpected during a fifth next period (5NP), and zero divisional filingsexpected during a sixth next period (6NP).

There are 0.67 legal placeholder conversion (LPC) filings expectedduring a current period (CP), 0.80 LPC filings expected during a firstnext period (1NP), 0.84 LPC filings expected during a second next period(2NP), 0.22 LPC filings expected during a third next period (3NP), 0.22LPC filings expected during a fourth next period (4NP), 0.12 LPC filingsexpected during a fifth next period (5NP), and 0.04 LPC filings expectedduring a sixth next period (6NP).

The growth and expense co-processor is operable to multiply theforecasted amounts shown by a fee table to determine forecasted expensesfor prosecution, issuances, and subsequent filings (e.g., with separateaccounting for attorney fees and government fees). The forecastedamounts of new provisional applications, utility applications, legalplaceholder inventions, and PCT applications can also be included in theforecast summary.

FIG. 260 is a diagram of an example of forecasted probabilities andtiming of receiving office actions, receiving notices of allowance, andof filing subsequent patent applications for a plurality of MTUs in theU.S. and in other countries of interest as determined by a growth andexpense co-processor of an improved computer for technology.

For example, for each market-tech unit (MTU) of market-tech units 1-x,domestic (e.g., U.S.) forecasting data (e.g., as discussed withreference to one or more of the previous Figures) and Country Σ throughCountry Ω forecasting data is determined for a current through sixthnext period. Countries Σ-Ω are countries of interest for each MTU andmay vary per MTU.

FIG. 261 is a schematic block diagram of an embodiment of an MTU patentplanning unit 362 of an improved computer for technology. The unit 362executes the MTU user application of MTU architectural patent protectionplan based on a variety of data that includes targeted patent position,subsequent filing practice, ideal patent protection, expense & growthdata, a calculated total number of inventions for the MTU, a calculatednumber of invention types, a calculated total number of inventions perphase, a calculated number of invention types per phase, a calculatednumber of remaining inventions to be invented, and a calculated numberof remaining inventions to be invented per remaining phase.

The patent planning unit 362 determines a target patent position and asubsequent (sub.) patent filing practice from the patent businessobjectives, which are received from an authenticated and authorized usercomputing device. The patent business objectives include one or more ofdesired patent position, desired patent spend per year, productdevelopment roadmap, technology development roadmap, etc.

The patent planning unit 362 determines ideal patent protection based onthe calculated total number of inventions for the MTU, the calculatednumber of invention types, the calculated total number of inventions perphase, and the calculated number of invention types per phase. The idealnumber of inventions corresponds to a percentage of the total number ofinventions that should be patent protected; not every inventions needsto be or should be patent protected. The ideal number of inventions thatshould be patented protected will typically be in the range of 60% to95% of the total number of inventions.

The unit 362 generates an architectural patent protection plan for anMTU to obtain patent protection in one or more countries. Thearchitectural patent protection plan includes a period-by-period (wherea period is a definable duration of time and is often defined to be ayear) plan. For a period, the plan includes the number of new patentapplications to be filed per country and per application type, thenumber of inventions to patent protect broken down by invention typesand per country, the number of office actions to be received percountry, the number of issuances to be received per country, the numberof subsequent patent application filings per type and per country,maintenance fees to be paid, and annuity fees to be paid.

The expense & growth data is interactive with the architectural patentprotection plan. Thus, as the specific numbers of the plan changes, theexpense & growth data changes. This allows for the architectural patentprotection plan to be adjusted as often as needed to adapt to changes inthe development of the technology, market adoption of the technology,productization of the technology, economic conditions, and so on.

FIG. 262 is a schematic block diagram of an example of creating anarchitectural patent protection plan by an improved computer fortechnology. This example includes an MTU environment & use data sectionfeeding an invention data section from which the architectural patentprotection plan is created. The MTU environment & use data sectionincludes the sub-sections of previous generation (PG) MTU data, currentgeneration (CG) MTU data, next generation (NG) MTU data, generationdata, existing patent data, and patent business data.

Each of the generation MTU data sub-sections includes the relevantinformation regarding an MTU database record and, at a minimum, includesthe general description of the MTU, its unique value propositions, itsmarketable features, and it technical challenges. The generation datasub-section includes data for each generation (e.g., start of thegeneration, end of the generation, and the duration of each phase of thegeneration). The existing patent data sub-section includes dataregarding existing patent applications, existing issued patents, andtheir patent holders (e.g., inventors, assignees, applicants).

The patent business data sub-section includes data regarding quantities(QTY) and/or ratios regarding the invention types of fundamentalinventions (FUN), commercially necessary (CN) inventions, and commercialexpansion (CE) inventions. The fundamental inventions include initialfundamental inventions and new fundamental inventions. The commerciallynecessary inventions include the initial commercially necessaryinventions and new commercially necessary inventions. The commercialexpansion inventions include the initial CE inventions, new CEinventions, vertical integration inventions, horizontal integrationinventions, potential acquirer inventions, competitor speed bumpinventions, potential standard essential inventions, and patent standardnon-essential but commercially necessary inventions.

The patent business data sub-section further includes data regarding thelikely use factors for the invention types of fundamental inventions(FUN), commercially necessary (CN) inventions, and commercial expansion(CE) inventions. For example, a normalized likely use factor for a CEinvention is 1, a normalized likely use factor for a CN invention is2.5, and a normalized likely use factor for a FUN invention is 4.5.

The patent business data sub-section further includes data regardingS-curve data for the invention types of fundamental inventions (FUN),commercially necessary (CN) inventions, and commercial expansion (CE)inventions. The patent business data sub-section further includes dataregarding duration of each generation and the corresponding phases.

The patent business data sub-section further includes data regardinggeneration to generation technology complexity factors (e.g., acomparison of the number of technical challenges and the tech challengeto inventive embodiment mappings). The patent business data sub-sectionfurther includes data regarding generation to generation disruptionfactor. The disruption factor scales from incremental throughbetter-mouse-trap through evolutionary to revolutionary (e.g., 1 forincremental and 10 for revolutionary, with the center of abetter-mouse-trap being a 3 and the center of evolutionary being a 7).

The invention data includes the total number of inventions likely to becreated for each of the generations; the number of existing issuedpatent for each generation; the number of pending patent application foreach generation; the number of legal placeholder inventions (LPI)inventions (e.g., enabled in pending patent application but not yetclaimed) for each generation; the inventions per phase of an S-curve foreach generation; and the timing of each generation and the phasesthereof. As described in greater detail with reference to subsequentfigures, the improved computer generates the architectural patentprotection plan for an MTU.

FIG. 263 is a schematic block diagram of an embodiment of existing andforecasting MTU patent landscape and competitor analysis units 342, 344,352, and 354 of an improved computer for technology. In high-level blockdiagram form, the units retrieve data and analyze the retrieved data toproduce an MTU patent landscape report and a patent holder report withrespect to the MTU.

The retrieve data includes MSBT data regarding the MTU and patent dataregarding the MTU. The patent data includes patent use data, generalinformation about the patents (e.g., patent ID data), patentclassification data (e.g., IPC classification), patent owner data,and/or claim element data.

The MTU patent landscape report includes rows for the previous, current,and next generations and columns for phase, existing inventioninformation (existing), a list patent holders (by who), and forecastedinvention information (forecasted). The existing invention informationincludes a total number of inventions, an ideal number of inventions,and an actual number of inventions protected. The forecasted inventioninformation includes a total number of inventions, an ideal number ofinventions, and a targeted number of invention to patent protect.

The patent holder report includes rows for each patent holder andsub-rows for each generation. The report includes columns for patentholder ID, tendencies, MTU, generation (GEN), number of inventionsprotected (QTY), quality of patent protection, patent position, marketpresence, phase, and estimated value.

FIG. 264 is a schematic block diagram of an example of data used by theMTU patent landscape and competitor analysis units 342, 344, 352, and354 of an improved computer for technology. The patent landscape dataincludes an invention data section, a patent data section, a previousgeneration (PG) section, a current generation (CG) section, and a nextgeneration (NG) section. The invention data, the patent data, and thegenerational data are similar to the invention data and generationaldata of FIG. 262 .

The patent landscape report data (i.e., the resulting data for a reportas shown in the previous figure) includes an MTU totals per generationdata section and a top owners data section. The MTU totals pergeneration data section includes data for each generation regarding atotal number of inventions to be created, the number of inventionsprotected to date, generation completed, number of issued patents todate, number of pending patent applications to date, a forecasted numberof patents to issue, a forecasted number of patent applications to befiled, the number of fundamental inventions that have been patentprotected and that are forecasted to be patent protected, the number ofcommercially necessary inventions that have been patent protected andthat are forecasted to be patent protected, and the number of commercialexpansion inventions that have been patent protected and that areforecasted to be patent protected.

The top owners data section includes, for each owner, the owner's name,the number of the owner's issued patents to date, the number of theowner's pending patent applications to date, a forecasted number ofpatents to issue to the owner, a forecasted number of patentapplications to be filed by the owner, the number of fundamentalinventions that have been patent protected and that are forecasted to bepatent protected attributable to the owner, the number of commerciallynecessary inventions that have been patent protected and that areforecasted to be patent protected attributable to the owner, and thenumber of commercial expansion inventions that have been patentprotected and that are forecasted to be patent protected attributable tothe owner.

FIG. 265 is a diagram of an example of data used by an MTU patentplanning unit and MTU patent landscape and competitor analysis units ofan improved computer for technology. The patent planning data includesMSBTP (marketing, sales, business, technology, and/or patents) data, oldMTU problems, old MTU features, new MTU problems, new MTU features,number of existing patents, patent holder data, the total number ofinventions, the patent fee schedule, the S-curve phase data for existingpatents, S-curve phase data for new inventions, quantity and/or ratiosfor invention types, likely use factors for the invention types,generational data, ideal number of inventions to be patent protected,new to old (e.g., CG to PG) complexity factor, and new to old disruptionfactor.

The patent landscape data includes MSBTP data, old MTU problems, old MTUfeatures, the number of existing patents (e.g., inventions protected bysome form of patent protection), patent holder data, S-curve phase dataregarding the existing patents, the TAM for the MTU, the SOM as apercentage of TAM, and CAGR of TAM and/or SOM. The improved computer'suse of the data in this figure and the preceding figures is discussed ingreater detail with reference to one or more previous figures and/orwith reference to one or more subsequent figures.

FIG. 266 is a logic diagram of an example of a method for balance ofpatent spend and desired patent position to produce a multi-year plan topatent protect an MTU as performed by a co-processor of an improvedcomputer for technology. The method begins at step 1600 where theimproved computer obtains patent planning data. The method continues atstep 1602 where the improved computer generates a plurality ofmulti-year patent protection plans; one for each of a plurality ofpatent positions. The patent position is a measure of patent leveragewith respect to the MTU over others. It is a sliding scale from weak tosuperior, where, as an example, weak is a 1 and superior is a 10.

The method continues at step 1064 where the improved computercalculates, for each plan and on a year-by-year basis, the expenses thevalue of the MTU. The method continues at step 1606 where the improvedcomputer provides a graphical representation of each plan with respectto its year-by-year patent position, patent spend, and value. The methodcontinues at step 1608 where the improved computer determines whether ithas received (e.g., within some time window) a selection of one of theplans. If yes, the method continues at step 1610 where the improvedcomputer finalizes the selected plan.

If the answer to step 1608 was no, the method continues at step 1612where the improved computer determines whether it has received (e.g.,within some time window) an input regarding a desired patent positionthat was not part of the plurality of patent positions. If yes, themethod continues at step 1614 where the improved computer generates amulti-year patent protection plan for the MTU based on the desiredpatent position.

If the answer to step 1612 was no, the method continues at step 1616where the improved computer determines whether it has received (e.g.,within some time window) an input regarding a desired patent spend. Ifyes, the method continues at step 1618 where the improved computergenerates a multi-year patent protection plan for the MTU based on thedesired patent spend.

If the answer to step 1616 was no, the method continues at step 1620where the improved computer determines whether it has received (e.g.,within some time window) an input regarding a desired MTU value. If yes,the method continues at step 1622 where the improved computer generatesa multi-year patent protection plan for the MTU based on the desired MTUvalue. If not, the method continues at step 1624 where the improvedcomputer determines whether a time out for response has expired. If yes,the method is done. If not, the method loops back to step 1608.

FIG. 267 is a diagram of an example of value of an MTU based on level ofpatent protection as determined by a co-processor of an improvedcomputer for technology. In this example graph, the value of an MTU(e.g., quantified technology) is plotted versus level of patentprotection. The value ranges from cost of reverse engineering to maximumand the level of patent protection ranges from weak to superior. Asshown, if there is no patent protection for an MTU, its value is thecost of reverse engineering, which may be trivial to millions ofdollars. The maximum value is dependent on the impact the MTU has on themarket and the size of the market.

FIG. 268 is a logic diagram of an example of a method for determiningpatent position for an MTU as performed by a co-processor of an improvedcomputer for technology. The method begins at step 1630 where theimproved computer identifies a market-tech unit (MTU) as a quantifiablepiece of technology. The method continues at step 1632 where theimproved computer determines whether the MTU can be “owned” (e.g., asuperior patent position is still obtainable).

If yes, the method continues at step 1634 where the improved computerdetermines whether the user, via the user computing device, wants to ownthe MTU. For example, from the user's perspective, is the potential ROIworth the patent spend. If yes, the method continues at step 1636 wherethe improved computer generates an architectural patent protection planbased on a superior patent position.

If the answer to step 1634 was no, the method continues at step 1637where the improved computer determines whether the user wants any patentprotection for the MTU (e.g., receives information from the usercomputing device). If not, the method continues at step 1648 where theimproved computer does not put together a patent protection plan for theMTU (e.g., no patents). If yes, the method continues at step 1638 wherethe improved computer receives a desired patent position, which is lessthan a maximum superior position. The method continues at step 1640where the improved computer generates an architectural patent protectionplan based on the inputted patent position.

If the answer to step 1632 was no, the method continues at step 1642where the improved computer determines what position can still beachieved, the associated costs, and the calculated value. The methodcontinues at step 1644 where the improved computer determines whether topursue patent protection (e.g., generate a plan) based on a user input.If no, the method continues at step 1648 where the improved computerdoes not create a patent protection plan. If yes, the method continuesat step 1646 where the improved computer generates an architecturalpatent protection plan based on the available patent position.

FIGS. 269A through 269D are S-curve diagrams for an MTU regardingperformance, profitability, number of total inventions, and breadth ofinventions as used by and/or determined by a co-processor of an improvedcomputer for technology.

FIGS. 270A and 270B are S-curve diagrams for one generation of an MTUregarding a number of total inventions over the life of the MTU andbreadth of inventions over the life of the MTU with an overlay ofinvention types as used by and/or as determined by a co-processor of animproved computer for technology.

FIG. 271 is an S-curve diagram for three generations of an MTU regardingperformance as used by and/or determined by a co-processor of animproved computer for technology. To differentiate between thegenerations, orange is used for the previous generation, blue is usedfor the current generation, and red is used for the next generation.

FIG. 272A is a diagram of an example of relative value of a patent andpatent application regarding a pharmaceutical MTU over time as used byand/or determined by a co-processor of an improved computer fortechnology. To differentiate between an issued patent and a pendingpatent application, the curve for the issued patent is a dark red lineand the curve for the pending patent application is a blue line.

FIG. 272B is a diagram of an example of relative value of a patent andpatent application regarding a communication, information, and/orelectrical technology MTU over time as used by and/or determined by aco-processor of an improved computer for technology. To differentiatebetween an issued patent and a pending patent application, the curve forthe issued patent is a dark red line and the curve for the pendingpatent application is a blue line.

FIG. 273 is a diagram of an example of relative value of a patent andpatent application regarding an MTU based on a ratio of pending patentapplications to issued patents regarding the MTU as used by and/ordetermined by a co-processor of an improved computer for technology. Todifferentiate between an issued patent and a pending patent application,the curve for the issued patent is a dark red line and the curve for thepending patent application is a blue line.

FIG. 274 is a diagram of an example of relative value of a patent andpatent application regarding an MTU based on market adoption as used byand/or determined by a co-processor of an improved computer fortechnology. To differentiate between an issued patent and a pendingpatent application, the curve for the issued patent is a dark red lineand the curve for the pending patent application is a blue line.

FIG. 275 is a diagram of an example of timeline for an invention fromcreation to expiration of an issued patent as used by and/or determinedby a co-processor of an improved computer for technology. Within aperiod of time after the creation of an invention (e.g., 0.2 years to 1year), a patent application is filed for the invention. The patentprotection plan identifies invention types, their corresponding techchallenge to inventive embodiment mapping, and likely time frame fortheir creation. With this information, the creation of an invention andseeking patent protection for it is planned.

Two to four years after the patent application is filed, it issues.Sometime after the patent issues (e.g., 0 to 4 years or more), it isused. Knowing how the patent will likely be used, helps in shaping thepatent protection plan for an MTU.

FIG. 276 is a diagram of an example of a well balance and high qualitypatent portfolio using a fence analogy as would be produced by aco-processor of an improved computer for technology. In this example,fundamental inventions are represented as fence posts, commerciallynecessary inventions are represented by fence rails, and commercialexpansion inventions are represented by fence pickets.

Like an actual fence, a patent portfolio is intended to keep others outof a property. The fence should encircle the property and each sectionshould be of equal size and strength. The size and strength of the fencedepends on the value of the property being protected. The more valuable,the higher and/or stronger the fence. The more imbalanced the size andstrength of each section of a fence, the less effective the fencebecomes and making the smaller and weaker sections even more vulnerable.

FIG. 277 is a diagram of an example of an imbalanced and varying qualitypatent fence analogy as would be produced by a conventional patentprocess. This example includes three sections of a fence. The firstsection on the left includes an appropriate number of fence components(e.g., posts, rails, and pickets) but each is of poor quality, whichsignificantly weakens this section of the patent fence.

The second section in the middle includes too few fence components,which significantly weakens this section of the fence. The third sectionon the right includes too many fence components, which is overstrengthens this section of the fence. Thus, if one wanted nearunfettered access to at a least a portion of the allegedly protectedproperty, one would access via the first or second sections. Animbalanced patent protection of technology like in this example,adversely affects the value of the technology and compromises the patentposition.

FIG. 278 is a diagram of an example of a weak patent fence analogy aswould be produced by a small company using a conventional patentprocess. In this example, the thin-lined white fence componentsrepresent a superior patent position for an MTU that includes techchallenges A, B, and C. Note that a tech challenges helps define thetechnical boundaries of an MTU.

In this example, the inventions patent protected by the small companyare represented by the black fence components. From this example, thefew patented inventions provides little barrier to access the propertyof the MTU. As such, a small company would have a weak to very weakpatent position and the value of the MTU is significantly less that itshould be.

FIG. 279 is a diagram of an example of an imbalanced and varying qualitypatent fence analogy as would be produced by a large company using aconventional patent process. The gray shaded fence components representthose owned by the large company, the black shaded fence componentsrepresent those owned by a small company, and the thin-lined whiteshaded component represent the components of a superior patent position.As in FIG. 277 , the first section of the fence for tech challenge Aincludes an appropriate number of inventions that have poor qualitypatent protection; the middle section for tech challenge B has too fewcomponents; and the third section for tech challenge C has too manycomponents.

FIG. 280 is a diagram of another example of a well balance and highquality patent fence analogy for an MTU as would be produced by aco-processor of an improved computer for technology. In this fenceanalogy that encircles an MTU and its evolving innovation to covermarket expansion of the MTU and/or technology expansion of the MTU. Eachsection of the fence corresponds to a tech challenge, which includessub-sections for each problem. Each problem sub-section includes one ormore inventive embodiments (e.g., inventions of one of the inventiontypes). To create a well-balanced and high quality patent fence aroundthe MTU, technical challenges as identified, and as them emerge, isanalyzed to create the tech challenge to inventive embodiment mapping.From this mapping, one or more inventive embodiments per problem isidentified for patent protection. The percentage of inventiveembodiments for a tech challenge to patent protect varies depending thenature of the tech challenge, the features it enables, and/or the uniquevalue propositions it supports. As an example, a tech challenge thatenables highly marketed features that drive sales will have a highpercentage of inventive embodiments patent protected (e.g., 50% to100%). As another example, a tech challenge that does not directlyenable marketable features or that does not directly support a UVP, willhave a lower percentage of inventive embodiments patent protected (e.g.,10% to 60%).

FIG. 281 is a diagram of another example of a well balanced and highquality patent fence analogy as would be produced by a co-processor ofan improved computer for technology. In this example, the various marketand/or technology expansion of a current generation of an MTU comprisesthe property to be protected. The segments to protect include coreconcepts of the MTU, expanded core MTU concepts, uses of the MTU,expanded uses of the MTU, MTU inclusion integration, MTU compositionintegration, standards for MTU, and MTU same tier integration.

FIG. 282 is a diagram of another example of a well balanced and highquality patent fence analogy as would be produced by a co-processor ofan improved computer for technology. In this example, eight MTUsconstitute a product and/or service. Each of the eight MTUs has its ownwell-balanced and high quality patent fence. Note that one of the MTUsmay be regarding combining the other MTUs to produce the product and/orservice.

FIG. 283 is a diagram of another example of a well balanced and highquality patent fence analogy as would be produced by a co-processor ofan improved computer for technology. This example illustrates that acurrent generation MTU builds on one more previous generation MTUs(e.g., market tech unit that represents a quantified technology).

FIG. 284 is a diagram of another example of a well balanced and highquality patent fence analogy as would be produced by a co-processor ofan improved computer for technology. This example illustrates that anext generation MTU builds on one or more current generation MTUs, whichbuild on one more previous generation MTUs (e.g., market tech unit thatrepresents a quantified technology). The evolution of technology fromone generation to the next is factored into planning patent protectionfor an MTU.

FIG. 285 is a diagram of an example of relative total number ofinventions and an ideal number of inventions for an MTU that providedata points for a well balanced and high quality patent portfolio aswould be produced by a co-processor of an improved computer fortechnology. To differentiate between a total number of inventions and anideal number of inventions, the curve for the total number of inventionsis a dark red line and the curve for the ideal number of inventions is ablue line.

The total number of inventions for an MTU is calculated based on thetechnical challenge to inventive embodiment mapping for each technicalchallenge of the MTU. The technical challenge to inventive embodimentmapping includes the technology challenge, one or more problems of thetechnical challenge, one or more solutions per problem, and one or moreinventive embodiments. As such, a technical challenge could have oneinventive embodiment (e.g., patentable inventions) to tens of inventiveembodiments (e.g., 20 to 100).

The improved computer interprets the technical challenge in light of theunique value proposition(s) it supports (directly and indirectly), themarketable features it enables (directly and indirectly), the nature ofthe technical challenge (e.g., commonalities with other known technicalchallenges), and/or the documentation defining the technical challengeto calculate the number of problems likely to be solved to fulfill thetechnical challenge.

The improved computer then defines a problem in terms of one or moreinventive concepts based on the data it used to calculate the number ofproblems. If the data substantiates identifying implementation elements,implementation mechanisms, and implementation variants for an inventiveconcept, the improved computer calculates them and calculates solutionsthat can likely be derived therefrom. If the data does not substantiatemaking a calculation, the improved computer estimates a number ofimplementation elements, a number of implementation mechanisms, and anumber of implementation variants. From there, the improved computerestimates the number of solutions that be derived therefrom. Theestimations are based on historical data of comparable technicalchallenges (e.g., reducing power consumption of a battery-powered watchis comparable to reducing power consumption of a battery-power vehicle).The more comparable technical challenges to draw from, the more accuratethe estimate will likely be.

The improved computer continues the estimations down to the inventiveembodiment level for each of the solutions for each of the inventiveconcepts for each of the problems of a technical challenges. Theimproved computer sums the estimated number of inventive embodiments foreach of the technical challenges to produce a total number ofinventions. The improved computer then maps the total number ofinventions to a normalized invention S-curve.

The improved computer calculates the ideal number of inventions that arelikely to be patent protected as discussed above. As technicalchallenges evolve, as new technical challenges emerge, as problems pertechnical challenge evolve, as problems for a technical challengeemerge, and so on, the improved computer updates the total number ofinventions likely to be invented and the ideal number of inventions topatent protect.

FIG. 286 is a diagram of another example of relative total number ofinventions and an ideal number of inventions for an MTU that providedata points for a well balance and high quality patent portfolio aswould be produced by a co-processor of an improved computer fortechnology. To differentiate between a total number of inventions, anideal number of inventions, fundamental inventions, commerciallynecessary inventions, and commercial expansion inventions, the curve forthe total number of inventions is a black line, the curve for the idealnumber of inventions is a red line, the curve for the fundamentalinventions is a blue line, the curve for the commercially necessaryinventions is a gold line, and the curve for the commercial expansioninventions is a purple line.

The curves are representative of cumulative inventions over time. Thetotal number of inventions is calculated as discussed above. From thetotal number of inventions and invention type data, the improvedcomputer calculates the total number of fundamental inventions, thetotal number of commercially necessary inventions, and the total numberof commercial expansion inventions. Generally, about 7.5% of the totalinventions are fundamental and are typically created in the create anddeploy phases, which account for about 20% to 25% of the life of theMTU; about 12.5% of the total inventions are commercially necessary andare typically created in the create deploy, and early optimize phases,which account for about 25% to 35% of the life of the MTU; and about 80%of the total inventions are commercial expansion and are typicallycreated in the deploy through mature phases, which account for about 70%to 75% of the life of the MTU. From these estimates, when about 70% ofthe life has expired, over 90% of the inventing has been done.

In this example, the ideal patent number is calculated from the totalnumber of fundamental inventions, the total number of commerciallynecessary, and the total number of commercial expansion. In equationform, the ideal number=a*FUN+b*CN+c*CE. The coefficients corresponds topercentage of the invention types that are likely to be patentprotected. For example, “a” ranges from 75% to 100%; “b” ranges from 60%to 100%; and “c” ranges from 40% to 90%. The improved computerdetermines the value for the coefficients based on a variety of factors,including, but not limited to, patenting traits of the entitiesdeveloping the MTU, market impact of MTU, level of disruption, life ofthe MTU, versatility of the MTU, etc.

FIG. 287 is a diagram of an example of invention type quantity andtiming for inventions of an MTU that provide data points for a wellbalance and high quality patent portfolio as would be produced by aco-processor of an improved computer for technology. In this example,the number of inventions is plotted against the technology life, both ofwhich are expressed in percentages. To differentiate between fundamentalinventions, commercially necessary inventions, and commercial expansioninventions, data regarding fundamental inventions is colored blue, dataregarding commercially necessary invention is colored gold, and dataregarding commercial expansion is colored red.

As shown in this figure, the blue fundamental inventions are createdearly in the technology life and very few, if any, occur beyond the 40%of the technology life expiring. As is also shown, the gold commerciallynecessary inventions are created early in the technology life and veryfew, if any, occur beyond the 60% of the technology life expiring. As isfurther shown, the red commercial expansion inventions are createdthroughout the technology life, peaking at the end of the optimize andthe beginning of the mature phase. The red commercial expansioninventions also account for a majority of all inventions (e.g., about70% to 85%).

FIG. 288 is a diagram of another example of invention type quantity andtiming for inventions of an MTU that provide data points for a wellbalanced and high quality patent portfolio as would be produced by aco-processor of an improved computer for technology. This diagramillustrates market expansion of a MTU over time. When an MTU is firstconceived, it is conceived for a particular purpose (e.g., as a newproduct, as a component of a new product, as a component of an improvedproduct, etc.).

Accordingly, the technical problem(s) and corresponding inventiveembodiment mapping is based on the core concepts for the MTU. Theimproved computer expands on the core concepts of the MTU by estimatingthe likelihood of new features, new functions, improved performance, newuses, vertical and/or horizontal integration, better reliability, betterefficiency, and/or other expansions of the core concepts. As discussedabove, as time passes, the concentration of invention type changes.Early in the life of the MTU, the blue fundamental inventions are mostprevalent. As time passes, the blue fundamental inventions fade fromdominance and the gold commercially necessary inventions are mostdominant. As more time passes, the gold commercially necessaryinventions fade, and the red commercial expansion inventions dominate.

FIG. 289 is a diagram of an example of expanding inventions of a techchallenge associated with an MTU that provide data points for a wellbalanced and high quality patent portfolio as would be produced by aco-processor of an improved computer for technology. In this diagram foran MTU, the initial core tech challenges are identified. The improvedcomputer analyzes the core tech challenges to determine if one or moreof them may relate to an existing standard or have the potential to bepart of a new standard. For example, if the tech challenge is related todigital communication between two devices, which do not have to bemanufactured by the same entity, then there is a potential that thedigital communication could become a standard.

For tech challenges that relate, or potentially relate, to a standard,the problems are identified. Each problem is analyzed by the improvedcomputer to determine if would be essential to the standard or notessential but likely commercially necessary. The improved computerrecords the resulting analysis in the MTU's database record.

The improved computer attempts to calculate new tech challenges from thecore tech challenges. The new tech challenges, or problems thereof, canrelate to potential acquirer integration of the MTU, competitor use ofcomparable MTUs, vertical up or down integration (e.g., MTU inclusion ofMTU composition), and/or horizontal integration.

The improved computer further attempts to calculate improved techchallenges from the core tech challenges. For example, the improvedcomputer attempts to calculate alternate uses of the MTU and/or the coretech challenges being applicable to other MTUs. If so, the improvedcomputer calculates alternate use problems and/or other MTU problems.

FIG. 290 is a diagram of an example of a graph that plots how well anMTU is patent protected with respect to its value as used by and/ordetermined by a co-processor of an improved computer for technology.This is an example for an evolutionary type products that includes oneor more MTU. The graph plots how well patent protect in percentage ofthe ideal number of inventions to patent protect versus the value of theMTUs of the product in percentage of the market opportunity (e.g., aportion of the TAM or the SOM).

As mentioned, the value of an MTU without patent protection is the costof reverse engineering. For this example, as the percentage of idealnumber increases, the value increases. Recall that the ideal numbercorresponds to inventions of the total number of inventions over thelife of the MTU to be patent protected. Thus, 100% of ideal is all ofthe inventions patent protected for the life of technology. A superiorpatent position can be generally obtained with a 35% to 60% of idealnumber of inventions patent protected.

FIG. 291 is a diagram of an example of a graph that plots various levelsof how well an MTU is patent protected with respect to its value as usedby and/or determined by a co-processor of an improved computer fortechnology. This graph plots an MTU's value as a percentage of marketopportunity versus inventing completed, where both axis are labeled withpercentage. The various curves represent different levels of patentprotection with respect to the ideal number of inventions based on theexample of FIG. 290 .

Color is used to differentiate the curves. A dark green line represents100% of ideal; a blue line represents 90% of ideal; a red linerepresents 80% of ideal; a purple line represents 70% of ideal; a yellowline represents 60% of ideal; a green line represents 50% of ideal; adark blue line represents 30% of ideal; a brown line represents 30% ofideal; a light purple line represents 20% of ideal; and an orange linerepresents 10% of ideal.

Each of the curves (10% to 100% of ideal) is calculated based on theequation of c*(1/[1+e{circumflex over ( )}x]), where x=a*(inventingpercentage −0.35), where “a” is an S-curve shaping factor that is anumber greater than equal to or greater than 5.0 and “c” is a scalingfactor based on the percentage of ideal and a tech driven marketdifferentiator factor “f”. The value for “f” ranges from 0.01 to 1.0,where a value of 1.0 indicates that all of the market value of isbecause of the technology of the MTU. For an evolutionary technology,the “f” factor is likely to be in the range of 0.3 to 0.7. The “c”coefficient is calculated based on the “f” factor and the percentage ofideal. For example, c=percentagerm, where “m” is equal to or greaterthan 1 and represents the level of competition in the marketplace andwhat it takes to have a superior patent position.

FIG. 292 is a diagram of another example of invention type quantity andtiming for inventions of an MTU that provide data points for a wellbalance and high quality patent portfolio as would be produced by aco-processor of an improved computer for technology. The graph of thisfigure plots percentage of inventions versus percentage of technology(MTU) life. The plotted data is for cumulative total number ofinventions to be created, cumulative ideal number of inventions topatent protect, time based relative quantity of fundamental inventionsto be created, time based relative quantity of commercially necessaryinventions to be created, and time based relative quantity of commercialexpansion inventions to be created.

To differentiate between fundamental inventions, commercially necessaryinventions, and commercial expansion inventions, data regardingfundamental inventions is colored blue, data regarding commerciallynecessary invention is colored gold, and data regarding commercialexpansion is colored red. To differential between the total number andideal number of inventions, a black line represents the total number ofinventions to be created and a purple line represents the ideal numberof inventions to be patent protected.

The graph indicates that about 70% of inventions will be created withinthe first half of the technologies life and that it occurs somewhere inthe late optimize phase or the early mature phase. The graph alsoindicates that almost all of the creation of fundamental inventionsoccur within the first 20% of life, which corresponds to the createphase and at least a portion of the deploy phase. The graph alsoindicates the relative quantities and timing for the creation ofcommercially necessary inventions and commercial expansion inventions.

The improved computer uses this data in a variety of ways. For example,the improved computer uses this data based on the current date todetermine the percentage of life that has transpired to date, the totalnumber of inventions that should have been created to date and brokendown based on invention types, and the ideal number of inventions thatshould have some form of patent protection to date and broken down basedon invention type. As a further example, the improved computer uses the“to date” data to determine what level of patent position can beachieved going forward.

FIG. 293 is a diagram of an example of relative use weighting of variousinvention types as used by and/or determined by a co-processor of animproved computer for technology. The invention types includesfundamental, commercially necessary, and commercial expansion aspreviously discussed. The relative use weighting factor is reflective ofan answer to the question of “can a comparable and commercially viableproduct or service be made without using the patented invention types?”

In general, it would be very difficult to create a comparable andcommercially viable product without using most of the fundamentalinventions, thus it gets a higher score than the other two inventiontypes. It would be difficult to create a comparable and commerciallyviable product without using a majority of the commercially necessaryinventions, thus it gets a higher score than the commercial expansionbut a lower score than fundamental inventions. Since commercialexpansion inventions expand the features, functions, uses, etc. it isprobable that a comparable and commercially viable product can becreated without using a majority of commercial expansion inventions. Itis not probable that a comparable and commercially viable product can becreated without using some of the commercial expansion inventions.

For this example, fundamental inventions have a use weighting factor of4.5; commercially necessary inventions have a use weighting factor of2.5; and commercial expansion inventions have a use weighting factor of1.0. As such, a fundamental invention is 4.5 times more likely to beused than a commercial expansion invention and a commercially necessaryinvention is 2.5 times more likely to be used than a commercialexpansion invention.

This example also shows the percentage range of invention types of thetotal number of inventions to be created. For example, fundamentalinventions typically account for 7.5% to 10% of the total number ofinventions to be created over the life of an MTU; commercially necessaryinventions typically account for 10.0 to 14.5% of the total number ofinventions; and commercial expansion inventions typically account for75.5% to 82.5% of the total number of inventions.

FIG. 294 is a diagram of another example of invention types' quantityand timing for inventions of an MTU that provide data points for a wellbalanced and high quality patent portfolio as would be produced by aco-processor of an improved computer for technology. In this example, anormalized annual number of inventions is plotted against the technologylife. To differentiate between fundamental inventions, commerciallynecessary inventions, and commercial expansion inventions, dataregarding fundamental inventions is colored blue, data regardingcommercially necessary invention is colored gold, and data regardingcommercial expansion is colored red.

The graph also includes two curves: one for a desired patent protectiondevelopment plan and the other for a delayed start in patent protectinginventions. Once the opportunity for patent protection has passed (e.g.,the invention has been publicly disclosed and is barred by patent law),it cannot be recaptured. With a slow start, many of the fundamentalinventions and commercially necessary inventions are no longer able tobe patented. Thus, to make up for it, more commercial expansioninventions need to be patented to achieve a desired patent position.

As an example, with a desired start and with the desire of building asuperior patent portfolio, an architectural patent protection plan wouldtarget patenting 40% to 60% of the ideal number of fundamentalinventions, 30% to 50% of the ideal number of commercially necessaryinventions, and 15% to 35% of the ideal number of commercial expansioninventions. As another example, with a delayed start and with the desireof building a superior patent portfolio, an architectural patentprotection plan could target patenting only 5% of the ideal number offundamental inventions, could target patenting only 10% of the idealnumber of commercially necessary inventions, and would have to make upfor it by targeting 35% to 65% of the ideal number of commercialexpansion inventions.

FIG. 295 is a diagram of another example of invention type quantity andtiming for inventions of an MTU that provide data points for a wellbalance and high quality patent portfolio as would be produced by aco-processor of an improved computer for technology. The diagramincludes a phase timeline regarding invention creation of create,deploy, optimize, and mature, which is divided into a past portion and afuture portion based on present time. The diagram further includestiming of invention types with respect to the phase timeline. Forexample, a majority of fundamental inventions are created during thecreate and optimize phases; a majority of the commercially necessaryinventions are created from mid create phase to early optimize phase;and a majority of the commercial expansion inventions are created frommid deploy phase through mature phase.

Each of the invention types are identified based on one or more solutiontrees (i.e., the mapping of technical challenges to problems toinventive concepts to implementation factors to solutions to inventiveembodiments). As time passes and forecasted technical challenges turninto existing or known technical challenges, forecasted problems turninto existing problems, forecasted inventive concepts turn into existinginventive concepts, forecasts implementation factors turn into existingimplementation factors, forecasted solutions turn into existingsolutions, and/or forecasted inventive embodiments turn into existinginventive embodiments, the data transforms from forecasted numbers forthe invention types and forecasted subject matter into actual number offor the invention types (actual patent protected numbers and/or o shouldhave been patent protected numbers) and into specific subject matter.

FIG. 296 is a diagram of an example of a graph that plots value of anMTU and costs to patent protect the MTU as used by and/or determined bya co-processor of an improved computer for technology. This graph plotsnormalized value of a patent protected MTU versus the percentage of theideal number of inventions to patent protect. The graph includes twocurves: one for the value of the MTU (e.g., quantified technology) andanother for the cost of patent protection.

As shown, and as based on an early start to patent protection, the valueincreases exponentially as the percent of the ideal number increases.The cost of patent protection increases linearly as the percent of theideal number increases. For a delayed start, the value curve stops atthe remaining percentage of the ideal number. For example, if the patentprotection started after 30% of the ideal number has passed, then 70%remains. Thus, the curve would stop at the value corresponding to 70%.The cost of patent protection for this example would have a steeperslope than shown to achieve the corresponding value curve. Basically,have to spend more on patenting protecting more commercial expansioninventions to make up for the slow start.

FIG. 297 is a diagram of an example of a graph that plots an early startof patent protecting a product (its evolution, its expanded technology,and/or its expanded uses) that includes multiple MTUs with a later startof patent protecting the product as used by and/or determined by aco-processor of an improved computer for technology. In this example,the improved computer determined that the ideal number for inventions topatent protect for the life of the multiple MTUs is 3,450 and thatpatent protecting 32% of the ideal number of inventions, broken down perMTU and by invention types, would provide the desired patent position.Thus, the target number of inventions to patent protect is about 1,100,assuming an early start to patent protection.

The graph plots number of inventions patent protected versus life of thetechnology as expressed in percentages. The graph also plots how wellpatent protected (HWP) percentage versus the tech life percentage. Thegraph includes a solid black line to represent a curve of how wellpatent protected for the 32% of ideal and starting the patent protectionearly (e.g., near the beginning of the create phase). The graph alsoincludes a dashed black line to represent a curve of the accumulatednumber of inventions being patent protected for the 32% of ideal andstarting the patent protection early.

The graph also includes a solid gray line to represent a curve of howwell patent protected for the late start to patent protection (e.g.,start near the beginning of the optimize phase). The graph also includesa dashed gray line to represent a curve of the accumulated number ofinventions being patent protected for the late start. For the late startto catch up to the how well patent protected, which directly correlatesto the value of the MTUs, about 1,350 inventions need to be patentprotected (about 250 more, which at a cost of approximately $28K perissued patent, this adds a cost of patent protection by $7 million).

In addition to more patent applications to prepare, file, and prosecute,the catching up does not occur until sometime in the mature phase. Foran acquisition of a company, the delay in catching up due to the latestart could result in the acquisition pricing being tens to hundreds ofmillions of dollars less than had the early start approach been used.

FIG. 298 is a diagram of another example of a graph that plots an earlystart of patent protecting the MTUs of FIG. 297 with a later start ofpatent protecting the MTUs as used by and/or determined by aco-processor of an improved computer for technology. In this example,the cost for patent protecting the 1,100 inventions for the early start,at $28K per patent protected invention, totals $30.8 million. The costsfor patent protecting the 1,350 inventions for the late start, at $28Kper patent protected invention, totals $37.8 million.

FIG. 299 is a diagram of another example of a graph that plots an earlystart of patent protecting the MTUs of FIG. 297 with a later start ofpatent protecting the MTUs as used by and/or determined by aco-processor of an improved computer for technology. This diagramfocuses on the first half of life of the MTUs to compare the numberinventions patent protected for the early start and the delayed start.

At the 10% of life mark, the early start has protected about 105inventions and the delayed start has protected about 25 inventions. Thisyields a difference of 80 inventions, which at a filing cost of $10K perinvention, is a difference in patent spend of $800K during the first 10%of life (e.g., 1 years to 3 years). At the 20% of life mark, the earlystart has protected about 240 inventions and the delayed start hasprotected about 67 inventions. This yields a cumulative difference of173 inventions, which at a filing cost of $10K per invention, is adifference in patent spend of $1,730 K ($800K from the first 10% and$930K from the second 10%).

At the 30% of life mark, the early start has protected about 380inventions and the delayed start has protected about 102 inventions.This yields a cumulative difference of 278 inventions, which at a filingcost of $10K per invention, is a difference in patent spend of $2,780 K($800K from the first 10%, $930K from the second 10%, and $1,030K fromthe third 10%).

At the 40% of life mark, the early start has protected about 555inventions and the delayed start has protected about 321 inventions.This yields a cumulative difference of 234 inventions, which at a filingcost of $10K per invention, is a difference in patent spend of $2,340 K($800K from the first 10%, $930K from the second 10%, $1,030K from thethird 10%, and −$430K from the fourth 10%).

At the 50% of life mark, the early start has protected about 755inventions and the delayed start has protected about 649 inventions.This yields a cumulative difference of 126 inventions, which at a filingcost of $10K per invention, is a difference in patent spend of $1,260 K($800K from the first 10%, $930K from the second 10%, $1,030K from thethird 10%,−$430K from the fourth 10%, and −$1,080 from the fifth 10%).

The difference in how well patent protected is 2.6% at 20% of life; 2.8%at 30% of life; 2.6% at 40% of life; and 1.2% at 50% of life. For amarket impact value of $1 billion the 2.6% different represents a valuedifference of $26 million; for a market impact value of $5 billion the2.6% different represents a value difference of $130 million; for amarket impact value of $10 billion the 2.6% different represents a valuedifference of $260 million; for a market impact value of $20 billion the2.6% different represents a value difference of $520 million; and for amarket impact value of $50 billion the 2.6% different represents a valuedifference of $1.30 billion.

At 40% of life, the cumulative patent spend difference was $2.34million. For the extra spend, the ROI for a market impact value of $1billion is 11.11 (e.g., 26/2.34); the ROI for a market impact value of$5 billion is 55.55 (e.g., 130/2.34); and so on.

FIG. 300 is a diagram of another example of a graph that plots an earlystart of patent protecting an MTU with a later start of patentprotecting the MTU as used by and/or determined by a co-processor of animproved computer for technology. The graph plots MTU value in millionsof dollars versus the life of the MTU in percentages. The graph alsoplots the how well patent protected versus the life of the MTU inpercentages. The graph further includes an acquisition or IPO window,which ranges from about 25% of life to 60% of life. The graph stillfurther includes two curves: one for the early start and the other forlate start.

At the opening of the acquisition or IPO window at 25% of life, thedifference in how well protected is about 2.8% and at the close of thewindow, the difference is about 0.4%. For a market impact value of $15billion, the MTU value at 10% is $1.5 billion. At the 25% of life mark,the 2.8% different represents a $420 million difference in MTU value.

FIG. 301 is a diagram of an example of six patent applications issuancerate based on statistics of a conventional patent process. On a filingdate, six patent applications were filed; applications 1-6. According topatent statistics, about ⅓ of patent applications filed are eventuallyabandoned (i.e., they do not issue). The color bule is used to clearlyindicate patent applications that will issue, and the color red is usedto clearly indicating the patent applications that will not issue (i.e.,abandoned).

Also shown in this figure is that, on average, 2.5 office actions arefiled for each patent application whether it issues or not. Forinstance, three offices were issued and responded for red line patentapplication #1 before it was abandoned; two offices were issued andresponded for blue line patent application #2 before it issued; threeoffices were issued and responded for blue line patent application #3before it issued; three offices were issued and responded for blue linepatent application #4 before it issued; two offices were issued andresponded for red line patent application #5 before it was abandoned;and two offices were issued and responded for blue line patentapplication #6 before it issued.

FIG. 302 is a diagram of an example of expenses for the six patentapplications of FIG. 301 . The fees for this figure include $15K forfiling a patent application (attorney fees and governmental filingfees), $4.5K for each office action response (attorney fees), and $2.5Kfor each patent issuance (attorney fees and governmental issuance fees).For the filing of the 6 patent application, an expense of $90K wasincurred.

Each of the six patents received a first office and a response was filedand an expense of $27K was incurred. Each of the six patents alsoreceived a second office and a response was filed; two of which issued,and one was abandoned, and an expense of $33K was incurred. Three of thesix patents also received a third office, and a response was filed; twoof which issued, and one was abandoned, and an expense of $18.5K wasincurred.

The total expense for all six patents was $168.5K. The average expensefor each of the six patents was $28K ($168.5K/6). The average cost perissued patent is $42K ($168.5K/4). In the years preceding the filing ofthis disclosure, the USPTO receives about 600,000 new patentapplications per year. With approximately ⅓ of them becoming abandoned,that is 200,000 patent applications filed per year on patents that willnot issue. With an average expense of $28K per patent application filed,about $5.6 billion spent annually on patent applications that will notissue. With the US accounting for about 30% of worldwide patentapplication filings, the annual worldwide spend on non-issued patents isabout $18.7 billion.

Of the patents that do issue, it is estimated that 60% have little to novalue due to poor quality, over-patenting a technical area,under-patenting a technology, or patenting ideas that have littlecommercial value. Thus, in the US, about 240,000 of the 400,000 patentsthat issues annually, have little to no value. At $28K per patentapplication filed, about $6.7 billion spent on patent applications thatresult in patents that have little to no value. With the US accountingfor about 30% of worldwide patent application filings, the annualworldwide spend on patent applications that result in patents that havelittle to no value is about $22.3 billion.

FIG. 303 is a diagram of an example of data for a period of anarchitectural patent protection plan for an MTU as used by and/ordetermined by a co-processor of an improved computer for technology. Foreach period (e.g., a year) and for each country in which patentprotection is sought, on a period-by-period basis for multiple periodsfor a patent protection plan, the improved computer calculates thenumber of fundamental inventions to be patent protected from theprevious generation (PG), from the current generation (CG) and/or fromthe next generation (NG); calculates the number of commerciallynecessary inventions to be patent protected from the previous generation(PG), from the current generation (CG) and/or from the next generation(NG); and calculates the number of commercial expansion inventions to bepatent protected from the previous generation (PG), from the currentgeneration (CG) and/or from the next generation (NG).

For the period, the improved computer further calculates a total numberof new invention to patent protect via new patent applications to befiled (e.g., the sum of PG, CG, and/or NG fundamental inventions, of PG,CG, and/or NG commercially necessary inventions, and of PG, CG, and/orNG commercial expansion inventions). The improved computer calculates anannual expense for patent protecting the total number of new inventionsbased on a patent application filing costs, the number of new patentapplications being filed, and the total number of new inventions. Theimproved computer may break down the annual numbers to monthly numbers.

For the period, the improved computer further calculates the number ofsubsequent patent application filings based on the expected issuancesduring the period and subsequent filing parameters. The subsequentfiling parameters include a first set of parameters for the issuance ofa utility patent application and a second set of parameters for theissuance of a subsequent filing patent application. The first set ofparameters includes a subsequent filing percentage, which could bedifferent for different types of inventions. For example, the subsequentfiling percentage is in the range of 10% to 150% for all inventiontypes. For a percentage over 100%, more than one subsequent filing will,on average, be filed from an issuing original utility patentapplication. As a specific example, for a subsequent filing percent of150%, for 10 issuing original utility patent application, 15 subsequentpatent applications (e.g., CON, CIP, DIV, LPC) will be filed.

As another example, each invention type has its own subsequent filingpercentage. As a specific example, fundamental inventions have asubsequent filing percentage of 100%; commercially necessary inventionshave a subsequent filing percentage of 80%; and commercial expansioninventions have a subsequent filing percentage of 50%.

The first set of parameters further includes subsequent filing typepercentage breakdown. For example, legal placeholder conversion patentapplications (LPC) have a first percentage; continuation patentapplications (CON) have a second percentage; continuation-in-part patentapplications (CIP) have a third percentage; and divisional patentapplications (DIV) have a fourth percentage, where the sum of the first,second, third, and fourth percentages equals 100%. Note that a legalplaceholder conversion patent application is regarding an invention thatwas disclosed in the original utility patent application but notclaimed. For subsequent filing decisions, a legal placeholder conversionpatent application is treated like an original utility patentapplication.

As an example of the first set of parameters, the subsequent filingpercentage is 166.6666% for all invention types, the LPC percentage is75%, the CON percentage is 15%, the CIP percentage is 5%, and the DIVpercentage is 5%; totaling 100%. Thus, for 12 issuing original utilitypatent applications, 20 subsequent patent application will be filed(e.g.,12/1.666); of which, 15 will be LPCs, 3 will be CONs, 1 will be aCIP, and 1 will be a DIV.

The second set of parameters for the issuance of a subsequent filingpatent application (e.g., child, grandchild, etc. of an original utilityor LPC patent application) includes a subsequent filing percentage and asubsequent filing type percentage breakdown. As an example of the secondset of parameters, the subsequent filing percentage is 66.6666% for allinvention types, the LPC percentage is 75%, the CON percentage is 15%,the CIP percentage is 5%, and the DIV percentage is 5%; totaling 100%.Thus, for 30 issuing subsequent patent applications, 20 subsequentpatent application will be filed (e.g.,12/1.666); of which, 15 will beLPCs, 3 will be CONs, 1 will be a CIP, and 1 will be a DIV.

For the calculated subsequent patent application filings, the improvedcomputer calculates annual quantities and annual expenses. The improvedcomputer may further determine monthly quantities and monthly expenses.

The improved computer further calculates the number of office actionresponses expected to be prepared and filed in the period. The computeralso calculates an annual expense for office action responses. Theimproved computer may further determine monthly quantities and monthlyexpenses for office action responses.

The improved computer further calculates the number of issuancesexpected to occur in the period. The computer also calculates an annualexpense for issuances. The improved computer may further determinemonthly quantities and monthly expenses for issuances.

The improved computer further calculates the number of maintenance fees(including annuities) expected to occur in the period. The computer alsocalculates an annual expense for maintenance fees. The improved computermay further determine monthly quantities and monthly expenses formaintenance fees.

FIG. 304 is a diagram of an example of parameter inputs for generating aperiod by period plan for patent protecting an MTU as used by and/ordetermined by a co-processor of an improved computer for technology.This diagram includes three sections: one for invention protection; asecond for US parameters, and a third for foreign national parameters.

The invention protection section includes rows corresponds to periods(e.g., a definable duration of time such a calendar year, a fiscal year,etc.) and columns for the number of inventions to be protected perperiod, the number of inventions per patent application, the number ofUS provisional patent applications to be filed, the number of US utilitypatent applications to be filed, the number of PCT applications to befiled, and the number of foreign national (FN) patent applications to befiled. As discussed herein, the invention protection inputs aredetermined by the improved computer. As an alternative, the improvedcomputer receives one or more inputs for this section from a usercomputing device, enabling the user of the computing device to test theimpact on the plan, the value, and/or the cost of changing one or moreinputs.

The US section includes office action (OA) probabilities, issuanceprobabilities, and subsequent filing inputs. As discussed herein, theimproved computer calculates the various inputs for this section. As analternative, the improved computer receives one or more inputs for thissection from a user computing device, enabling the user of the computingdevice to test the impact on the plan, the value, and/or the cost ofchanging one or more inputs.

The foreign national (FN) section includes common parameters andindividual country parameters. The common parameters include US to FNfiling inputs and PCT or direct to foreign national. The US to FN filinginput is a percentage of inventions that are to be patent protected inforeign national countries with respect to the number to be US patentprotected. Each country sub-section includes office action (OA)probabilities, issuance probabilities, and subsequent filing inputs. Asan alternative to each country having its own parameters, one set ofparameter is used for all countries of interest.

As discussed herein, the improved computer calculates the various inputsfor the foreign section. As an alternative, the improved computerreceives one or more inputs for this section from a user computingdevice, enabling the user of the computing device to test the impact onthe plan, the value, and/or the cost of changing one or more inputs.

FIG. 305 is a diagram of an example of a period of a multiple periodplan for patent protecting an MTU as used by and/or determined by aco-processor of an improved computer for technology. For each period ofa plan, the improved computer summarizes the quantities and cost ofexecuting the plan for the period and for the cumulation of periods thathave passed. For the present period, the improved computer summariesannual and monthly quantities and costs for new US patent applicationsto be filed, the number of inventions to be patent protected, the numberof US office actions expected to be received, the number of US issuancesexpected to be received, the number of US CON applications expected tobe filed, the number of US CIP applications expected to be filed, thenumber of US DIV applications expected to be filed, the number of US LPCapplications expected to be filed, the number of US maintenance feesthat are due, the number of PCT applications expected to be filed, thenumber of new foreign national applications expected to be filed, thenumber of foreign national office actions expected to be received, thenumber of foreign national issuances expected to be received, the numberof foreign national subsequent filing (SF) patent applications expectedto be filed, and the foreign application annuities that are due.

The improved computer generates the cumulative section to include asummary of the to date quantities and costs for US patent applicationsthat have been filed, the number of inventions that have been patentprotected, the number of US office actions that have been received, thenumber of US issuances that have been received, the number of US CONapplications that have been filed, the number of US CIP applicationsthat have been filed, the number of US DIV applications that have beenfiled, the number of US LPC applications that have been filed, thenumber of US maintenance fees that have been paid, the number of PCTapplications that have been filed, the number of new foreign nationalapplications that have been filed, the number of foreign national officeactions that have been received, the number of foreign nationalissuances that have been received, the number of foreign nationalsubsequent filing (SF) patent applications that have been filed, and theforeign application annuities that have been paid.

FIG. 306 is a diagram of an example of a private database record for aninvention of an MTU as used by and/or determined by a co-processor of animproved computer for technology. In this diagram, the improved computerexecutes the patent plan execution tracking unit 368 to generate arequest for the creation of an invention-patent record of a privatedatabase and generates the data to populate the record. In addition, theimproved computer executes the patent plan execution tracking unit 368to generate an MTU snapshot report (e.g., the “to-date data of thepreceding Figure) and to generate a patent plan compliance report.

To generate the patent compliance report, the improved computer comparesthe planned patent protection activities to the actual patent protectionactivities. For example, the improved computer compares the targetednumber of inventions to patent protect for a period with the number ofinventions that have been patent protected. If there is a difference,the report highlights the difference (e.g., ahead of pace forcommercially necessary invention for tech challenge 1, behind pace forfundamental inventions for tech challenge 2, etc.). As another example,the improved computer compares the number of office actions excepted tobe received per the plan and the number of office actions that have beenreceived. If there is a difference, the report highlights thedifference. The improved computer interprets received versus expectedoffice actions differences to determine if changes are needed to theoffice action parameters.

The invention-patent records includes sections for invention docketinginformation, patent holder information, patent docketing information,invention information, and MTU information. The invention informationincludes fields for an invention score, generation data, status, andinvention type. The invention score is a measure of importance to patentprotect based on invention type, tech challenge, portfolio fit, novelty,and/or alternate usability.

The MTU section includes field headers of MTU name, tech challenge(s),problem(s), inventive concept(s), solution(s), and inventiveembodiment(s). For each of the field headers, the record includes one ormore fields. The data in this section is limited to data that isrelevant to the invention. As an example, the specific embodiment(s) ofa solution of an inventive concept of a problem of a technical challengeof an MTU is records, not all of the tech challenges, etc., of the MTU.

Referring next to FIGS. 307-362 , various improvements in theconfiguration and operation of data processing tools, techniques, datastructures, and devices that can be used for, among other things,determining and presenting technology valuations. In variousembodiments, the processing tools and devices perform technologyvaluations at the level of an MTU using techniques that rely on uniquecapabilities available only to processing devices, and which the humanmind is not practically adapted to perform. Various valuation techniquesdisclosed herein gather and analyze massive amounts of data, and usethat analysis to construct linked data structures to determine andpresent technology valuations at multiple different levels ofabstraction.

Such valuations include distilling massive amounts of information andpresenting it to users in an understandable format. In one sense, thisdistillation can be understood with reference to an internet searchengine, which distills information from the universe of availabledocuments into a simplified search result that an end-user canunderstand and use to make decisions. That is not to say the followingfigures disclose a search engine, but that the various improvementsdescribed herein arise in the context of large scale computational anddata processing systems, much like the Internet gives rise to the needfor search engines.

Referring now to FIG. 307 a portfolio valuation tool for valuing an MTUwill be discussed according to various embodiments of the presentdisclosure. Portfolio valuation tool 1650 can be implemented using aco-processor of an improved computer for technology, which includes atleast one computing device 120 (e.g., one or more of the embodiments ofFIGS. 6A-6G). In some embodiments, portfolio valuation tool 1650 is oneof multiple co-processors used by a primary computing device to executeone or more the functions of the computing entity. In other embodiments,portfolio valuation tool 1650 is implemented as a primary function of aprimary computing device.

Illustrated embodiments of portfolio valuation tool 1650 include marketimpact co-processor 1652, market-patent “k” factor co-processor 1656,and how well protected processor 1654. Market impact co-processor 1652includes market value evaluation unit 1658, PG market share evaluationunit 1660, MTU market takeover evaluation unit 1662, and MTU marketexpansion evaluation unit 1664. How well protected processor 1654includes portfolio evaluation co-processor 1666, which further includesissued patent evaluation unit 1670, patent quality unit 1672, remaininglife evaluation unit 1674, patent breadth evaluation unit 1676, patentbalance evaluation unit 1678, status ratio evaluation unit 1680; andinventions evaluation co-processor 1668, which further includes idealportfolio likely use evaluation unit 1682, actual portfolio likely useevaluation unit 1682, and actual portfolio likely use evaluation unit1684. Market impact co-processor 1652 receives input including MTUcorrelated financial data. How well protected processor 1654 receivesinput including MTU portfolio status and MTU patent landscape. Portfoliovaluation tool 1650 uses the outputs of market impact co-processor 1652,market-patent “K” factor co-processor 1656, and how well protectedprocessor 1654 to generate an MTU value. The MTU value output byportfolio valuation tool indicates the value of an evaluated MTU withrespect to one or more entities, where the MTU value is a function ofthe market impact of the MTU (e.g., market impact score), how well theMTU is protected (e.g., how-well-protected score), and a market leveragefactor (e.g. market-patent “k” factor).

In various embodiments, the market impact score represents a percentageof the Serviceable Addressable Market (SAM) attributable to the impactof the MTU; the how-well-protected score is based on patent positionstrength and patent portfolio quality; and the market-patent “k” factoris determined by comparing how necessary patent protection is for aparticular MTU vs. the level of competition within the MTU), and thenmultiplying that result by the market opportunity driven by the MTU.

Correlated financial data can be provided to portfolio valuation tool1650 in response to a request for input generated by Portfolio valuationtool 1650, in response to completion of a process that determines thecorrelated financial data, or the like. In various embodiments,previously determined correlated financial data can be obtained from oneor more MTU data records (e.g., FIG. 42A) included in in one or moredatabases, for example a marketing, sales, business, technology, andpatent (MSBTP) database (e.g., FIG. 53 ) in response to the request forinput. In other embodiments, another co-processor of the improvedcomputer for technology can execute a financial data correlation processin response to the request for input. In various embodiments,determining correlated financial data includes performing one or more ofa historical financial analysis, a financial trend financial analysis,or a financial forecast analysis at the MTU level. MTU portfolio statuscan be provided to portfolio valuation tool 1650 in response to arequest for input generated by Portfolio valuation tool 1650, inresponse to completion of a process that determines the MTU portfoliostatus, or the like. In various embodiments, previously determined MTUportfolio status can be obtained from one or more MTU data records(e.g., FIG. 42A) included in in one or more databases, for example amarketing, sales, business, technology, and patent (MSBTP) database(e.g., FIG. 53 ) in response to the request for input. In otherembodiments, another co-processor of the improved computer fortechnology can execute a portfolio status process in response to therequest for input.

MTU patent landscape input can be provided to portfolio valuation tool1650 in response to a request for input generated by Portfolio valuationtool 1650, in response to completion of a process that determines theMTU portfolio status, or the like. In various embodiments, previouslydetermined MTU portfolio patent landscape information can be obtainedfrom one or more MTU data records (e.g., FIG. 42A) included in one ormore databases, for example a marketing, sales, business, technology,and patent (MSBTP) database (e.g., FIG. 53 ) in response to the requestfor input. In other embodiments, another co-processor of the improvedcomputer for technology can execute a portfolio status process inresponse to the request for input.

In an example of operation of portfolio valuation tool 1650, consider acompany that is developing a touch screen technology. The output ofportfolio valuation tool 1650 would vary based on which MTU is used forthe evaluation. For example, when the MTU being considered is “cellphones,” the output of portfolio valuation tool 1650 is likely to bedifferent than when an the MTU being considered is “touch screens,”because the market for “cell phones” and “touch screens” is notco-extensive, and because the financial value of a “cell phone” islikely to be different than the financial value of a “touch screen.”Furthermore, if the company already has a patent portfolio, it isunlikely that the portfolio provides exactly equivalent protection for“cell phones” and “touch screens.” Perhaps the cell phone market has adifferent number of competitors. Maybe cell phone technology is more orless mature, more or less disruptive, and/or matures at a different ratethan the touch screen market. Maybe one of the two technologies issubstantially protected by patents owned by others. The MTU value outputby portfolio valuation tool 1650 takes any or all of these variousfactors, and more, into account by identifying relationships,quantifying, organizing, and analyzing these relationships and others toarrive at a data based MTU value that would not otherwise be possible todetermine to the same degree of precision in any practical amount oftime.

Referring next to FIG. 308 an embodiment of MTU valuation data used by aportfolio valuation tool for valuing an MTU as performed by aco-processor of an improved computer for technology will be discussed.MTU valuation data includes MTU data, which can be obtained from an MTUrecord included in one or more databases, such as MTU database 264 (FIG.152 ). MTU data includes information pertaining to an MTU, generally.MTU information can include, but is not limited to, information definingor describing an MTU, e.g. MTU boundaries, information linking the MTUto related MTUs, e.g. sub MTUs included in the MTU and higher-level MTUsin which the current MTU is included, scientific and technologicalcategories associated with the MTU, or the like.

MTU valuation data also includes data related to the market impact ofthe MTU, including but not limited to: total addressable market (TAM) ofmarket including the MTU; MTU effect on TAM, compound annual growth rate(CAGR) of TAM; serviceable obtainable market (SOM) of market includingthe MTU; MTU effect on SOM, compound annual growth rate (CAGR) of SOM;MTU market expansion data; MTU takeover data; “old” (e.g. known,existing, or previous tech offering data). The output of the marketimpact of MTU data can be used, in conjunction with “k” factor data(e.g. patent competitiveness data), to determine the “k” factor, amarket leverage factor.

How well protected data, includes, but is not limited to, portfolioscore information and invention score information. Portfolio scoreinformation includes the number of issued market-tech (m-t) patents,number of pending m-t patent applications, number of legal placeholder(LPI) m-t inventions, patent quality indicator/rank/rating, patent agedata, MTU portfolio breadth data, and MTU portfolio balance data.

Invention score data includes data indicating one or more of a number ofideal inventions, a number of protected inventions, or invention curvedata. In various embodiments, the invention score data includesinformation indicating whether an invention is fundamental (FUN)invention, a commercially necessary (CN) invention, or a commercialexpansion (CE) invention.

Referring next to FIG. 309 another embodiment of a portfolio valuationtool for valuing an MTU as performed by a co-processor of an improvedcomputer for technology will be discussed. The patent portfoliovaluation uses one or more of the following data types (referred toherein as patented MTU valuation data) to generate an MTU value.Additional data types may also be used. The patented MTU valuation dataincludes patent data, patent protection data, previous generation (PG)MTU data, current generation (CG) MTU data, next generation (NG) MTUdata, and market impact data. Although the portfolio valuation tool maydirectly obtain and use this information in some embodiments, in otherembodiments some or all of these data types may be precalculated byexternal processing systems and stored in one or more databases, fromwhich the portfolio evaluation tool can obtain them in response to aquery, in response to periodic or a-periodic updates, in response touser inputs and/or queries, or the like.

In addition to the data types discussed above, external data employed bysubsystems, processing modules, and/or co-processors included in thepatent portfolio valuation tool to generate an MTU valuation can also beconsidered to be patented MTU valuation data. Note that the term“patented MTU valuation data” does not require the data to be patented,but refers to the fact that at least one technology within an MTU isdisclosed in a patent or patent application, or is considered as apotential subject of one or more patent applications. For example, oneor both of marketing, sales, business, and finance (MSBF) informationand technology information can be used by a market impact dataco-processor in conjunction with market impact data to generate PG, CG,and NG market impact results for an MTU under consideration. Similarly,patent use information can be used in conjunction with patent dataand/or patent protection data by a patent protection data co-processorto generate PG, CG, and NG market impact results for an MTU underconsideration. Market impact data includes, but is not limited to MTUTAM/SOM data, MTU effect on TAM/SOM data, CAGR or TOM/SOM data; PG % ofTAM/SOM data, CG % of TAM/SOM data, NG % of TAM/SOM data, CG takeover ofPG data, NG takeover of CG data, and/or market expansion data as aresult of CG MTU.

Patent data includes, but is not limited to data related to patents,patent applications, and legal placeholder inventions (LPIs). Patentdata can also include patent holder data, which indicates, among otherthings entities to whom a patent has issued or is assigned.

Patent protection data includes the number of issued market-tech (m-t)patents, the number of protected inventions, number of ideal inventions,invention curve data, number of pending m-t patent applications, numberof legal placeholder inventions (LPIs) patent quality data patent agedata, m-t portfolio breadth data, m-t portfolio balance data, patenttransaction data (e.g. licensing information; pending and completedlitigation pleadings, motions, and rulings; patent prosecution data(e.g. number of office actions; office actions and responses; appeal andreply briefs; and appeal decisions), or the like.

PG MTU data, CG MTU data, and NG MTU data each include market-tech (m-t)data related to their respective generations. Player data is alsoincluded for each of the PG MTU data, CG MTU data, and NG MTU data.Player data refers to companies designing, selling, manufacturing,operating, servicing, or otherwise involved in a particular MTU. Forexample, some of the “players” in the “electric vehicle charger” MTUcould be Shell®, Siemens®, Tesla®, Schneider Electric®, and ABB®.

Patent portfolio valuation co-processor used the output of the marketimpact data co-processor, patent protection data co-processor, the PGMTU data co-processor, the CG MTU data co-processor, and the NG MTU dataco-processor to generate one or more patented MTU valuations. In theillustrated example, patent portfolio valuation co-processor calculatesa PG market impact value, a CG market impact value, an NG market impactvalue, a PG how well protected value, a CG how well protected value, andan NG how well protected value. These values are used as a basis forgenerating a PG portfolio value, a CG portfolio value, and an NGportfolio value, which in turn can be used as a basis for determining anMTU value. In some embodiments, any or all of the values determined bypatent portfolio valuation can be output as the final MTU value andprovided to one or more other co-processors for further processing,transmitted to a GUI on a user interface device, used to update one ormore MTU records included in a database, or the like. In the illustratedexample, the PG portfolio value is calculated by multiplying the PGmarket value by the PG how well protected value. Similarly, the CGportfolio value is calculated by multiplying the CG market value by theCG how well protected value, and the NG portfolio value is calculated bymultiplying the NG market value by the NG how well protected value.

Referring next to FIG. 310 another embodiment of a portfolio valuationtool for valuing an MTU as performed by a co-processor of an improvedcomputer for technology will be discussed. The embodiment of portfoliovaluation tool 1650 illustrated in FIG. 310 includes a market impactco-processor 1690, a how well protected co-processor 1692, a “k” factorco-processor 1694, a reverse engineering co-processor 1696, a valuecalculation co-processor 1698, an ROI calculation co-processor 1700, andan expense and growth unit co-processor 364.

Portfolio evaluation tool 1650 determines a first tech value using atech value for MTU based on existing patent unit 350, and a second techvalue using a tech value for MTU based on forecasted patent unit 350.

The tech value for MTU based on existing patent unit 350 includes atleast one or more of the following: an existing patents market impactMTU unit 348, which can be implemented using a market impactco-processor 1690, and which generates a market wide SOM value of theexisting patent MTU; a how well MTU is protected by existing patentsunit 346, which can be implemented using a how well protectedco-processor 1692, and which generates a value (e.g. from 0 to 1)representing how well the MTU is protected by existing patents; a “k”factor co-processor 1694, which generates a “k” value (e.g. from 0.1 to0.9, with 0.6 being typical for communication, information, electronictechnologies); and a reverse engineering co-processor 1696, whichgenerates a reverse engineering costs value associated with the MTU. Theoutput of the tech value for MTU based on existing patent unit 350 isprovided to value calculation co-processor 1698.

The tech value for MTU based on forecasted patent unit 360 includes atleast one or more of the following: a forecasted patents market impactMTU unit 358, which can be implemented using a market impactco-processor 1690, and which generates a market wide SOM value of theforecasted patents MTU; a how well MTU is protected by forecastedpatents unit 356, which can be implemented using a how well protectedco-processor 1692, and which generates a value (e.g. from 0 to 1)representing how well the MTU will be protected by forecasted patents; a“k” factor co-processor 1694, which generates a “k” value (e.g. from 0.1to 0.9, with 0.6 being typical for communication, information,electronic technologies); and a reverse engineering co-processor 1696,which generates a reverse engineering costs value associated with theMTU. The output of the tech value for MTU based on forecasted patentunit 360 is provided to value calculation co-processor 1698.

Value calculation co-processor 1698 determines a value of the MTU byadding the value of the MTU based on existing patent protection to thevalue of the MTU based on forecasted future patent protection. Valuecalculation co-processor 1698 also determines the value of the MTUwithout any patent protection based on the cost of reverse engineeringdetermined by the reverse engineering co-processor 1696. The value ofthe MTU with and without patent protection are transmitted to ROIcalculation co-processor 1700.

ROI calculation co-processor 1700 also receives existing patent expenseinformation and forecasted future patent expense information fromexpense and growth unit 364, and uses that information in conjunctionwith the value information received from value calculation co-processor1698 to determine a return on protection investment. In at least oneembodiment, the return on protection investment is determined bydividing the value of the MTU by the cost of protecting the MTU. In someimplementations, the return on protection investment also takes intoaccount the difference between the difference between the value of theMTU with and without patent protection.

Referring next to FIG. 311 an embodiment of an MTU how well patentprotected co-processor of a portfolio valuation tool for valuing an MTUof an improved computer for technology will be discussed. MTU how wellprotected co-processor 1692 includes a how well MTU is protected byexisting patent units 346 and a how well MTU is protected by forecastedfuture patent units 356.

How well MTU is protected by existing patent unit 346 determines howwell the MTU is protected by existing patents by multiplying a portfoliofactors score for existing patents by the invention scope factors forexisting patents. In various embodiments, a portfolio factor score forexisting patents ranges from about 0.02 to 1. In those same embodiments,an invention scope factor for existing patents is in the range of about0.01 to 1.

How well MTU is protected by forecasted future patents unit 346determines how well the MTU is protected by forecasted future patents bymultiplying a portfolio factors score for forecasted future patents bythe invention scope factors for forecasted future patents. In variousembodiments, a portfolio factor score for forecasted future patentsranges from about 0.02 to 1. In those same embodiments, an inventionscope factor for forecasted future patents is in the range of about 0.01to 1.

MTU how well protected co-processor 1692 generates a combined portfoliofactor score using the portfolio factors score for existing patents andthe portfolio factors score for forecasted future patents, and acombined invention scope factors score using the invention scope factorsscore for existing patents and the inventions scope factors score forforecasted future patents. The combined portfolio factors score ismultiplied by the combined invention scope factors score to generate ahow well is MTU protected value.

Referring next to FIG. 312 an embodiment of a portfolio factors scorefor existing patents unit and a portfolio factors score for forecastedfuture patents unit of a portfolio valuation tool for valuing an MTU ofan improved computer for technology will be discussed. Portfolio factorsscore for existing patents unit 1702 determines a portfolio factorsscore associated with existing patents by multiplying an issued patentscore by the sum of the following scores: a quality score, a remaininglife score, a breadth score, a balance score, a pending to issued score,and an LPI percent score. In one example, the portfolio factors score isin the range of about 0.02 to 1, the issued patent score is in the rangeof about 0.02 to 1, the quality score is in the range of about 0.02 to0.25, the remaining life score is in the range of about 0.02 to 0.1, thebreadth score is in the range of about 0.02 to 0.25, a balance score isin the range of about 0.02 to 0.2, a pending to issued score is in therange of about 0.02 to 0.11, and a legal placeholder invention (LPI)percent score is in the range of about 0.02 to 0.1.

Portfolio factors score for forecasted future patents unit 1704determines a portfolio factors score associated with forecasted futurepatents by multiplying an issued patent score (associated withforecasted future patents) by the sum of the following scores (alsoassociated with forecasted future patents): a quality score, a remaininglife score, a breadth score, a balance score, a pending to issued scoreand an LPI percent score. In one example, the portfolio factors score isin the range of about 0.02 to 1, the issued patent score is in the rangeof about 0.02 to 1, the quality score is in the range of about 0.02 to0.25, the remaining life score is in the range of about 0.02 to 0.1, thebreadth score is in the range of about 0.02 to 0.25, a balance score isin the range of about 0.02 to 0.2, a pending to issued score is in therange of about 0.02 to 0.11, and a legal placeholder invention (LPI)percent score is in the range of about 0.02 to 0.1.

With the exception of the remaining life score and the LPI percentscore, the various component scores used by portfolio factor score forexisting patents unit 1702 and portfolio factors score for forecastedfuture patents unit 1704 are discussed in greater deal with respect toeither previous or subsequent figures.

The remaining life score is a factor indicating how long the patentportfolio will continue to provide protection for a particular MTU.Because a portfolio can consist of multiple different patents inmultiple jurisdictions, each having its own expiration date, theremaining life score can be used to represent an average, mean, ormedian time until expiration of patent protection. In some embodiments,the remaining life score may decrease at either an exponential or othervariable rate as more patents expire. For example, the remaining lifescore for a 400 patent portfolio may be 0.1, but expiration of halfthose patents will not necessarily result in a remaining life score of0.05 (half of 0.1).

The LPI percent score refers to the percentage of legal placeholderinventions (CPIs) included in the portfolio. CPIs refer to inventionsdisclosed, but not yet claimed (or fully claimed), in a patentapplication. For example, consider a patent application that disclosesmultiple different advancements in a touchscreen display technology(e.g. four different inventive circuits that can be used to implementthe touchscreen display, and an inventive controller that can be usedwith any of the inventive circuits). If a first application is filedclaiming one of the four different inventive circuits, the remainingthree inventive circuits and the inventive controller can be referred toas LPIs. Each LPI has the potential to mature into its own patent, so aportfolio that includes 100 patent applications, each having 3 LPIs hasthe potential to mature into 400 issued patents (100 applications+300LPIs) covering 400 different inventions, whereas a portfolio thatincludes 100 patent applications with very few LPIs would almostcertainly not mature into 400 issued patents covering 400 differentinventions.

In addition to generating portfolio factors scores for both existing andforecasted future patents, the portfolio valuation tool uses thosescores to generate an overall portfolio factors score. The portfoliovaluation tool combines the outputs of the portfolio factors score forexisting patents unit 1702 and the Portfolio factors score forforecasted future patents unit 1704 to generate an overall issued patentscore, an overall quality score, an overall remaining life score, anoverall breadth score, an overall balance score, an overall pending toissued score and an overall LPI percent score. The overall portfoliofactors score tool then generates the overall portfolio factors score bymultiplying the overall issued patent score by the sum of the followingscores: the overall quality score, the overall remaining life score, theoverall breadth score, the overall balance score, the overall pending toissued score, and the overall LPI percent score.

Referring next to FIG. 313 another embodiment of a portfolio factorscore for existing patents unit of a portfolio valuation tool forvaluing an MTU of an improved computer for technology will be discussed.Portfolio factors score for existing patents unit 1702 includes anissued existing patent score unit 1706 that calculates an issued patentscore according to various embodiments. Issued existing patent scoreunit 1706 obtains data to be included in an issued patent score tablefrom one or more data sources. Obtaining the data can include one ormore of issuing a query to a commercial, government, or specialtydatabase, performing data scanning and optical character recognition,receiving updated information periodically or in response to atriggering event. For example, one or more co-processors of an improvedcomputer system can be programmed to periodically query a database of apatent-related database. If a query of that database indicates that apatent application in a portfolio has issued, automatic transfer ofinformation indicating the patent issuance can be transmitted toportfolio factors score for existing patents unit 1702. In at least oneembodiment, the data obtained for the issued patent score table isgrouped into one or more time periods. The time periods can be, forexample, a year, a quarter, a month, a number of years, number ofquarters, number of months, or the like.

The time period can be determined in advance, and updated data can beobtained automatically one or more times each time period. In someembodiments, the time period can be specified by information included ina user query, or otherwise.

For a particular time period, issued existing patent score unit 1706sums the number of issued patents present in a portfolio over that timeperiod, sums the number of inventions protected over that time period,calculates the percentage of the number of patents in the portfolio thatissued over that time period, and calculates an issued patent score.Issued patent scores are calculated over each time period to beconsidered.

For example, if portfolio factors score for existing patents unit 1702is tasked with calculating issued patent scores for each two-year periodfrom 2023-2024, portfolio factors score for existing patents unit 1702will iteratively calculate 6 issued patent scores for the followingperiods: 2013-2014, 2015-2016, 2017-2018, 2019-2020, 2021-2022, and2023-2024.

Referring next to FIG. 314 is a diagram of another embodiment of aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology will be discussed. Portfolio factors score for forecastedfuture patents unit 1704 includes an issued forecasted future patentscore unit 1708 that calculates an issued patent score according tovarious embodiments. Issued forecasted future patent score unit 1708obtains data to be included in an issued patent score table from one ormore data sources. Obtaining the data can include one or more of issuinga query to a commercial, government, or specialty database, performingdata scanning and optical character recognition, receiving updatedinformation periodically or in response to a triggering event. Forexample, one or more co-processors of an improved computer system can beprogrammed to periodically query a database of a patent-relateddatabase. If a query of that database indicates that a patentapplication in a portfolio has issued, automatic transfer of informationindicating the patent issuance can be transmitted to portfolio factorsscore for forecasted future patents unit 1704. In at least oneembodiment, the data obtained for the issued patent score table isgrouped into one or more time periods. The time periods can be, forexample, a year, a quarter, a month, a number of years, number ofquarters, number of months, or the like.

The time period can be determined in advance, and updated data can beobtained automatically one or more times each time period. In someembodiments, the time period can be specified by information included ina user query, or otherwise.

For a particular time period, issued forecasted future patent score unit1708 sums the number of issued patents present in a portfolio over thattime period, sums the number of inventions protected over that timeperiod, calculates the percentage of the number of patents in theportfolio that issued over that time period, and calculates an issuedpatent score. Issued patent scores are calculated over each time periodto be considered.

For example, if portfolio factors score for forecasted future patentsunit 1704 is tasked with calculating issued patent scores for the next 2years in 4-quarter periods, portfolio factors score for forecastedfuture patents unit 1704 will iteratively calculate two issued patentscores for the following periods: Q1-Q4 of first upcoming year, Q1-Q4 ofsecond upcoming year.

Referring next to FIG. 315 an example of data for a portfolio factorscore for existing patents unit of a portfolio valuation tool forvaluing an MTU of an improved computer for technology will be discussed.In various embodiments, the data obtained by portfolio factors score forexisting patents unit 1702 (FIG. 313 ) includes data used to form datarecords for existing time period(s) that have been completed (e.g.previous year(s)), a current time period (CP) that has not yet beencompleted (e.g. the current year), and some number of “next periods”(NPs) (e.g. the next 7 years). In some embodiments the existing timeperiod(s), current time period, and next time periods need not be of thesame duration. Thus, the existing time period can be the past 4 years,while the current time period and the next time periods can each be asingle quarter.

The data obtained by portfolio factors score for existing patents unit1702 includes, but is not limited to, at least one of the following:number of issued patents, number of inventions protected, issued patentpercentage, and/or issued patent score. As illustrated, each row of datain the illustrated data structure for existing patents includesinformation linked to a particular period of time (e.g. existing, CP,1^(st)-7^(th) NP). The information in the rows can be organized andstored as a record within a database. For example the illustrated table(or some other data structure) can be stored within, or linked to, anMTU record. Similarly, some or all of the information can beindividually stored, or stored in other records linked to each otherusing relational database linking techniques. Note that the data used byportfolio factors score for existing patents unit 1702 can useforecasted data, despite the fact that the data is used by existingpatents unit 1702.

Referring next to FIG. 316 calculated data for a portfolio factors scorefor forecasted future patents unit of a portfolio valuation tool forvaluing an MTU of an improved computer for technology will be discussed.In various embodiments, the data obtained by portfolio factors score forforecasted future patents unit 1704 (FIG. 314 ) includes data used toform data records for existing time period(s), a current time period(CP) that has not yet been completed (e.g. the current year), and somenumber of “next periods” (NPs) (e.g. the next 7 years). In someembodiments the time periods need not be of the same duration.

The data obtained by portfolio factors score for forecasted futurepatents unit 1704 includes, but is not limited to, at least one of thefollowing: number of issued patents, number of inventions protected,issued patent percentage, and/or issued patent score. As illustrated,each row of data in the illustrated data structure for existing patentsincludes information linked to a particular period of time (e.g.existing, CP, 1^(st)-7^(th) NP). The information in the rows can beorganized and stored as a record within a database. For example theillustrated table (or some other data structure) can be stored within,or linked to, an MTU record. Similarly, some or all of the informationcan be individually stored, or stored in other records linked to eachother using relational database linking techniques. By contrast with thedata obtained by portfolio factors score for existing patents unit1702(FIG. 315 ), data obtained by portfolio factors score for forecastedfuture patents unit 1704 does not include an existing number of issuedpatents or an existing number of inventions protected, although theissued patent percentage and the issued patent score for an existingportfolio may be included.

Referring next to FIG. 317 a graph of issued patent percentage to issuedpatent score for valuing an MTU of an improved computer for technologywill be discussed. The horizontal axis of the graph represents an issuedpercentage for a portfolio with respect to an MTU, and the vertical axisrepresents an issued patent score for the same portfolio with respect tothe same MTU. The issued percentage is determined by dividing the numberof issued patents by the number of inventions protected. the issuedpatent score is determined by the following formula: issued patentscore=x+1-e″(issued percentage/exponent factor), where x is a minimumoffset.

Referring next to FIG. 318 another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology is illustrated. The data illustrated in FIG. 318 includesdata representing summations of data obtained by portfolio factors scorefor existing patents unit (FIG. 315 ), and the data obtained by theportfolio factors score for forecasted future patents unit (FIG. 316 ).The combined portfolio factors scores can be used by an MTU how wellpatent protected co-processor 1692 to generate an overall patent qualityscore.

It should be noted that the existing and future summed scores caninclude summed data that has been weighted prior to being summed. Insome embodiments, the forecasted future data (FIG. 316 ) be given more,or less, impact than the existing data (FIG. 315 ) by applying aweighting factor to some or all of the data. For example, the impact ofexisting data can be increased or decreased by multiplying by one ormore data values by one or more impact factors. For example, modifyingthe number of inventions protected for a current period by 1.004 willincrease the impact of that data, but multiplying that same data by0.096 will decrease the impact of that same data. One or more differentimpact factors can be applied to individual data items, to a subset ofdata items, or to the entire set of either or both existing andforecasted future data items.

Referring next to FIG. 319 , another embodiment of a portfolio factorscore for existing patents unit and a portfolio factor score forforecasted future patents units of a portfolio valuation tool forvaluing an MTU of an improved computer for technology will be discussed.As illustrated in FIG. 319 , a portfolio valuation tool for valuing anMTU of an improved computer for technology includes portfolio factorsscore for existing patents unit 1702, portfolio factors score forforecasted future patents unit 1704, and MTU how well patent protectedco-processor 1692.

Portfolio factors score for existing patents unit 1702 includes a firstquality score unit 1710, which generates the following scores: aninvention disclose and decide score, quality of patent applicationpreparation score, quality of patent application prosecution score, anda quality of issued patent score. Quality score unit 1710 combines thesescores to generate combined quality scores for existing patents, andprovides the combined quality scores for existing patents to MTU howwell patent protected co-processor 1692.

Providing the combined quality scores for existing patents can includedirect transmission to MTU how well patent protected co-processor 1692,transmission to an intermediary that forwards the combined quality scorefor existing patents, transmission to a storage unit for storage andlater retrieval by MTU how well patent protected co-processor 1692, orthe like. Generating the combined quality scores for existing patentscan include creating averages, sums, and trends, such as an issuancerate trend, a quality improvement trend, a quality decreasing trend, anumber of office actions (OAs) to issuance trend, or the like.

Portfolio factors score for forecasted future patents unit 1704 includesa second quality score unit 1712, which uses the quality score forexisting patents as proxy for the quality score for forecasted futurepatents, or forecasts the quality score for forecasted future patentsbased on the quality scores for existing patents. Forecasting thequality score for forecasted future patents can include the use ofvarious statistical methods, including but not limited to straight line,moving averages, simple linear regression, multiple linear regression.The data used for forecasting can include data obtained from qualitativedata sources (e.g. the Delphi method, market surveys, executive opinionsurveys, and the like) and/or data obtained quantitatively based on timeseries analysis and projection, and/or causal models.

MTU how well patent protected co-processor 1692 uses the outputs ofportfolio factors score for existing patents unit 1702 and portfoliofactors score for forecasted future patents unit 1704 to generate apatent quality score indicating how well an MTU is protected by aportfolio including existing and forecasted future patents.

Referring next to FIG. 320 another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology will be discussed. In particular, data used for generating aninvention disclose and decide score are discussed. As shown by FIG. 320, a score for each invention disclose and decide function (e.g. “topic”)can be calculated by quality score unit 1710 (FIG. 319 ). It should beappreciated in advance that the illustrated topics are not an exhaustivelist of topics that may be scored by various embodiments.

In at least some embodiments, a score is generated for the followingtopics: invention harvesting (ensuring inventions are identified/notoverlooked), advanced invention (identifying potential inventions byanalyzing opportunities for expanding current technologies), inventiontypes tracked (which types of inventions areprotected/yet-to-be-protected by particular patents/applications), techchallenges tracked (what technical challenges are anticipated forimplementing particular technologies), problems tracked (which problemsneed to solved in a particular technology), inventive concepts tracked(inventive concepts are basis of patent claim—there may be multipleinventive concepts for a particular MTU), solutions tracked (whichproblems have been solved by particular inventions), inventiveembodiments tracked (a single invention can have multiple embodiments),decision metric includes portfolio fit (do decisions includeconsideration of how well an invention fits within a current/forecastedfuture portfolio), decision metric others focused (are decisions basedon use of technology by others, and not solely on internal use), anddisclose and decide score (a composite score quantifyingstandardization, repeatability, and consistency of disclosure anddecision making processes with respect to technology protection). Thescore for each topic represents a degree to which policies for eachtopic have been established, and how well any established policies areimplemented.

In at least one such embodiment, each of the scores generated can be inthe range of 0.0 to 04. A value of 0.0 indicates that no policy has beenimplemented and/or that the policy is never enforced if it has beenimplemented. A value of 0.01 indicates that a policy related to a topicis in place, but that the enforcement of the policy is inconsistent. Avalue of 0.02 indicates that a policy related to a topic is in place andis repeatably enforced. A value of 0.03 indicates that a policy relatedto a topic is in place and enforcement of that policy has beenstandardized. A value of 0.04 indicates that both the policy is inplace, and enforcement of that policy, have been optimized.

For example, if there is no policy in place to track tech challenges ofa particular MTU as they relate to particular patents or patentapplications, the score for the track tech challenges topic will be 0.0.A score of 0.0 will also apply if there is a policy in place to tracktech challenges, but that policy is only sporadically followed orenforced. If a policy for invention harvesting is in place andrepeatably followed, the score for the topic of invention harvestingwould be 0.02. If policies regarding decision metrics are others focusedand enforcement of those decision metrics is standardized, the scoregiven to the topic of policies regarding decision metrics are othersfocused will be 0.03. If policies related to invention type tracking(e.g. tracking which invention types are covered by particular patentsand applications) are in place and enforcement is optimized (e.g.requiring entry of invention types into a database or docket trackingsystem, and periodically sending reminders if such data is not entered),the score for the topic of invention types tracked can be given a scoreof 0.04.

The invention disclose and decide score can be generated by summing thescores calculated for individual topics, by averaging those scores, bydetermining a median score, or by performing another statisticalanalysis. In some embodiments, the disclose and decide score itselfranges from 0.0 to 0.04, while in other embodiments, the disclose anddecide score can be up to the sum of all individual topic scores. Insome embodiments, any or all of the individual topic scores can beweighted relative to other topic scores so that adding the weightedindividual topic scores produces a sum between 0.0 and 0.04.

Referring next to FIG. 321 another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology will be discussed. In particular, data used for generating aquality of patent application preparation score and/or a quality ofissued patent score are discussed. As shown by FIG. 321 , a score foreach patent function (e.g. “topic”) can be determined by quality scoreunit 1710 (FIG. 319 ).

In at least some embodiments, a score is generated for the followingtopics: identifiable novelty nuggets, no unnecessary claim limitations,direct figure support for claims, direct spec support for claims,negligible structural issues with claims, spec includes technicalembellishment, no unnecessary spec limitations, include a generic claimsupport section, well written, support for subsequent filing(s), nofatal flaws with claims, and patent score. The score for each topicrepresents a degree to which each of the patent functions has beenachieved. It should be appreciated that the illustrated topics are notan exhaustive list of topics that may be scored by various embodiments.

In at least some embodiments, scores can be generated automatically,based on quantitative analysis of one or more patent documents. Forexample, direct figure support for claims and direct spec support forclaims can be identified based on textual analysis of the claims, thespecification, and the Figures to identify matching terms, consistentuse of terms in conjunction with callouts, and the like. Even scores forcertain topics that appear to more subjective can be automaticallygenerated based on textual analysis of one or more documents and/orcomparison with a listing of terms and associated concepts. Assume, forexample, that a claim element includes a novelty nugget associated witha given technology. All other elements of the claim can be compared to alisting of element types that may be necessary for the given technologyto be functional. If one of the other elements is not included in thelist, it can be identified as unnecessary, and/or flagged for furtherevaluation. In some embodiments, the scores are entered based on humananalysis of a patent or patent application. In yet further embodiments,an artificial intelligence (AI) bot can be trained to generate eachscore. In yet other embodiments, some combination of human, computerautomated scoring, and AI scoring is employed.

In at least one such embodiment, each of the scores assigned toindividual patent functions (topics) can be in the range of 0.0 to 0.06.A value of 0.0 indicates that a particular patent function hasdefinitely not been achieved, or is not present. If a particular patentfunction is present, but not fully achieved, a value of between 0.01 to0.05 is assigned, with 0.05 being more fully achieved. A value of 0.06indicates that a particular patent function has definitely beenachieved.

The total patent score, which represents a quality of patent applicationpreparation score and/or a quality of issued patent score can begenerated by summing the scores determined for one or more individualtopics, by averaging those scores, by determining a median score, or byperforming another statistical analysis. In some embodiments, the patentapplication preparation score itself ranges from 0.0 to 0.06, while inother embodiments, the total patent score can be up to the sum of allindividual topic scores. In some embodiments, any or all of theindividual topic scores can be weighted relative to other topic scoresso that adding the weighted individual topic scores produces a sumbetween 0.0 and 0.06.

The patent function of “no fatal flaws with claims” is an importantexception to the way in which the scores of individual patent functionsare used to generate the total patent score. If there are fatal flaws inthe claims, the total patent score will be assigned to be zero,regardless of any other scores.

Referring next to FIG. 322 another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology will be discussed. In particular, data used for generating aquality of patent application prosecution score. As shown by FIG. 322 ,a score for each patent prosecution function (e.g. “topic”) can bedetermined by quality score unit 1710 (FIG. 319 ).

In at least some embodiments, a score is generated for the followingtopics: number of office actions to issuances (too many office actionsindicates lack of clarity of invention), number of responses with claimamendments (too many office actions indicates lack of clarity ofinvention), succinct arguments (long arguments give rise to potentialestoppel issues), no unnecessary discussions (unnecessary discussionsgive rise to potential estoppel issues), no defamatory comments (couldcause enforcement issues), terminal disclaimer used properly (do notsurrender patent term unnecessarily or cause enforcement issues),applicant filed IDS (demonstrates candor), well written, no fatal flawswith claim amendments, and patent prosecution score. The score for eachtopic represents a degree to which each of the patent prosecutionfunctions has been achieved. It should be appreciated that theillustrated topics are not an exhaustive list of topics that may bescored by various embodiments.

Scores can be generated automatically, based on quantitative analysis ofpatent prosecution documents, for example those included in the officialfile history. Scores can be determined based on one or more of thefollowing: textual analysis of the claims, specification, figuresofficial actions, responses to official actions, appeal briefs, replybriefs, or interview summaries; comparison of prosecution documents tosample prosecution documents, sample arguments; comparison of a patentprosecution functions associated with a current analysis with patentprosecution functions associated with other patent prosecutions; humananalysis/user provided input; automated computer analysis and scoregeneration such as through the use of trained artificial intelligence(AI) bots, or some combination thereof.

In at least one such embodiment, each of the scores assigned toindividual patent prosecution functions (topics) can be in the range of0.0 to 0.06. A value of 0.0 indicates that a particular patentprosecution function has definitely not been achieved, or is notpresent. If a particular patent prosecution function is present, but notfully achieved, a value of between 0.01 to 0.05 is assigned, with 0.05being more fully achieved. A value of 0.06 indicates that a particularpatent prosecution function has definitely been achieved.

The total patent prosecution score, which represents a quality of patentapplication prosecution score, can be generated by summing the scoresdetermined for one or more individual patent prosecution functions(topics), by averaging those scores, by determining a median score, orby performing another statistical analysis. In some embodiments, thetotal patent prosecution score itself ranges from 0.0 to 0.06, while inother embodiments, the total patent prosecution score can be up to thesum of all individual topic scores. In some embodiments, any or all ofthe individual topic scores can be weighted relative to other topicscores so that adding the weighted individual topic scores produces asum between 0.0 and 0.06.

The patent prosecution function of “no fatal flaws with claimamendments” is an important exception to the way in which the scores ofindividual patent prosecution functions are used to generate the totalpatent prosecution score. If there are fatal flaws with the claimamendments, the total patent score will be set to zero, regardless ofany other scores.

Referring next to FIGS. 323 and 324 another embodiment of a portfoliofactor score for existing patents unit and a portfolio factor score forforecasted future patents units of a portfolio valuation tool forvaluing an MTU of an improved computer for technology will be discussed.In particular, a determination of a breadth score will be discussed.

A breadth score, when used in evaluating a portfolio, indicates abreadth of protection provided by a patent portfolio for a particularMTU, and is a function of the following: boundaries of an MTU,boundaries of planned uses of an MTU, boundaries of alternate uses of anMTU, and boundaries of other uses of an MTU.

A portfolio valuation tool for valuing an MTU of an improved computerfor technology determines breadth quality scores for existing patentsand forecasted future patents, and provides those scores to MTU how wellpatent protected co-processor 1692, which generates an overall breadthquality score and uses that overall breadth quality score to determinehow well an MTU is/will be protected by a patent portfolio consisting ofexisting patents and forecasted future patents. A higher overall breadthquality score will indicate that MTU boundaries are well defined, andwell expanded.

A portfolio valuation tool includes portfolio factors score for existingpatents unit 1702 and portfolio factor score for forecasted futurepatents unit 1704. Both portfolio factors score for existing patentsunit 1702 and portfolio factor score for forecasted future patents unit1704 include issued breadth score unit 1714.

The issued breadth score unit 1714 included in portfolio factors scorefor existing patents unit 1702 generates a previous generation scoreindicating a breadth of protection provided by an existing portfolio fora previous generation (PG) MTU and a current generation (CG) scoreindicating a breadth of protection provided by an existing portfolio fora current generation (CG) MTU. The two scores are combined to generate atotal existing patent breadth score by using a weighting factor of CG toPG based on a disruption of CG MTU, a level of innovation of the CG MTU,or the like. In at least one embodiment, the more disruptive andinnovative the CG technology is, the greater the weight assigned to theCG relative to the PG.

The breadth score unit 1714 included in portfolio factors score forforecasted future patents unit 1704 generates a remaining CG scoreindicating a breadth of protection provided by a forecasted portfoliofor a forecasted remaining life of the CG MTU and a next generation (NG)score indicating a breadth of protection provided by the forecastedfuture patent portfolio for a NG MTU. The two scores are combined togenerate a total forecasted future breadth score by using a weightingfactor of remaining CG to NG based on a disruption of CG MTU, a level ofinnovation of the CG MTU, or the like. In at least one embodiment, themore disruptive and innovative the CG technology is, the greater theweight assigned to the NG relative to the remaining CG.

Referring next to FIG. 325 another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology will be discussed. In particular, data used for generating aprevious generation score by portfolio factors score for existingpatents unit 1702 (FIG. 324 ) is illustrated. A score for each previousgeneration topic can be determined or obtained by Portfolio FactorsScore for existing patents unit 1702.

In at least some embodiments, a score is generated for the followingprevious generation topics: MTU offered in products in PG, MTU core techwell defined, MTU planned uses well defined, MTU extended core tech welldefined, MTU extended core tech uses well defined, MTU alternate useswell defined, MTU extended uses well defined, MTU uses by targeted otherwell defined, and MTU standards applicability well defined. The previousgeneration (PG) score is generated based on the individual topic scores.The score for each topic represents a degree to which each of theprevious generation topics has been achieved. A higher overall previousgeneration score indicates that MTU boundaries for the previoustechnology generation (previous generation of the MTU) are well defined,and well expanded. It should be appreciated that the illustrated topicsare not an exhaustive list of topics that may be scored by variousembodiments.

Scores can be generated automatically, based on one or more of thefollowing: textual analysis of the documents; comparison of documents tosamples; comparison of scores assigned to other previous generationMTUs, human analysis/user provided input; automated computer analysisand score generation such as through the use of trained artificialintelligence (AI) bots, or some combination thereof.

In at least one such embodiment, if no MTU is offered in a previousgeneration product, the total previous generation score will be 0. If anMTU is offered in a previous generation product, the range for eachfunction is 0.0 to 0.1. If the MTU cannot be extended (e.g. the MTU isfully extended already), the maximum score will be assigned for topicsrelated to MTU extension. Similarly, if there are no alternatives orstandards related to the MTU, the maximum score will be assigned fortopics related to MTU alternatives or standards.

The total previous generation score can be generated by summing thescores determined for one or more previous generation topics, byaveraging those scores, by determining a median score, or by performinganother statistical analysis. In some embodiments, the total previousgeneration score itself ranges from 0.0 to 0.1, while in otherembodiments, the total previous generation score can be up to the sum ofall individual topic scores. In some embodiments, any or all of theindividual topic scores can be weighted relative to other topic scoresso that adding the weighted individual topic scores produces a sumbetween 0.0 and 0.1.

Referring next to FIG. 326 is another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology will be discussed. In particular, data used for generating acurrent generation score by portfolio factors score for existing patentsunit 1702 (FIG. 324 ) or a remaining current generation score byportfolio factors score for forecasted future patents unit 1704 (FIG.324 ), is illustrated. A score for each CG (or remaining CG) topic canbe determined or obtained by Portfolio Factors Score for existingpatents unit 1702 and/or portfolio factors score for forecasted futurepatents unit 1704.

In at least some embodiments, a score is generated for the followingcurrent generation topics: MTU core tech well defined, MTU planned useswell defined, MTU extended core tech well defined, MTU extended coretech uses well defined, MTU alternate uses well defined, MTU extendeduses well defined, MTU uses by targeted other well defined, and MTUstandards applicability well defined. The current generation (CG) andremaining CG scores are generated based on the individual topic scores.Note that in some embodiments, a single CG score can be calculated, andsplit between CG and remaining CG based on a phase of the CG MTU. Thus,if the CG MTU has a life expectancy of 2 years, and this analysis isbeing performed 1.5 years into the life of the MTU, ¾ of the single CGscore can be assigned as the CG score, while ¼ of the CG score can betreated as the remaining CG score. Other suitable divisions are withinthe spirit and scope of this disclosure.

The score for each CG topic represents a degree to which each of the CGtopics has been achieved. A higher overall CG score indicates that MTUboundaries for the current technology generation (CG MTU) are welldefined, and well expanded. It should be appreciated that theillustrated topics are not an exhaustive list of topics that may bescored by various embodiments.

Scores can be generated automatically, based on one or more of thefollowing: textual analysis of the documents; comparison of documents tosamples; comparison of scores assigned to other previous generationMTUs, human analysis/user provided input; automated computer analysisand score generation such as through the use of trained artificialintelligence (AI) bots, or some combination thereof.

The range of scores for each function is 0.0 to 0.1. If the MTU cannotbe extended (e.g. the MTU is fully extended already), the maximum scorewill be assigned for topics related to MTU extension. Similarly, ifthere are no alternatives or standards related to the MTU, the maximumscore will be assigned for topics related to MTU alternatives orstandards.

The total CG score can be generated by summing the scores determined forone or more current generation topics, by averaging those scores, bydetermining a median score, or by performing another statisticalanalysis. In some embodiments, the total CG score itself ranges from 0.0to 0.1, while in other embodiments, the total CG score is the sum of allindividual topic scores. In some embodiments, any or all of theindividual topic scores can be weighted relative to other topic scoresso that adding the weighted individual topic scores produces a sumbetween 0.0 and 0.1.

Referring next to FIG. 327 a diagram of another example of calculateddata for a portfolio factor score for forecasted future patents units ofa portfolio valuation tool for valuing an MTU of an improved computerfor technology will be discussed. In particular, data used forgenerating a next generation (NG) score by portfolio factors score forforecasted future patents unit 1704 (FIG. 324 ), is illustrated. A scorefor each next generation (NG) topic can be determined or obtained byquality score unit 1712 included in portfolio factors score forforecasted future patents unit 1704.

In at least some embodiments, a score is generated for the following NGtopics: NG started, MTU core tech well defined, MTU planned uses welldefined, MTU extended core tech well defined, MTU extended core techuses well defined, MTU alternate uses well defined, MTU extended useswell defined, MTU uses by targeted other well defined, and MTU standardsapplicability well defined. The total NG score is generated based on theindividual topic scores.

The score for each NG topic represents a degree to which each of the NGtopics has been achieved. A higher overall NG score indicates that MTUboundaries for the next technology generation (NG MTU) are well defined,and well expanded. It should be appreciated that the illustrated topicsare not an exhaustive list of topics that may be scored by variousembodiments.

Scores can be generated automatically, based on one or more of thefollowing: textual analysis of the documents; comparison of documents tosamples; comparison of scores assigned to other previous generationMTUs, human analysis/user provided input; automated computer analysisand score generation such as through the use of trained artificialintelligence (AI) bots, or some combination thereof.

The range of scores for each function is 0.0 to 0.1. If the NG has notyet started, the total NG score will be set to 0. If the MTU cannot beextended (e.g. the MTU is fully extended already), the maximum scorewill be assigned for topics related to MTU extension. Similarly, ifthere are no alternatives or standards related to the MTU, the maximumscore will be assigned for topics related to MTU alternatives orstandards.

The total NG score can be generated by summing the scores determined forone or more next generation topics, by averaging those scores, bydetermining a median score, or by performing another statisticalanalysis. In some embodiments, the total NG score itself ranges from 0.0to 0.1, while in other embodiments, the total NG score is the sum of allindividual topic scores. In some embodiments, any or all of theindividual topic scores can be weighted relative to other topic scoresso that adding the weighted individual topic scores produces a sumbetween 0.0 and 0.1.

Referring next to FIGS. 328 and 329 another embodiment of a portfoliofactor score for existing patents unit and a portfolio factor score forforecasted future patents units of a portfolio valuation tool forvaluing an MTU of an improved computer for technology will be discussed.

A balance score, when used in evaluating a portfolio, indicates whethera patent portfolio provides balanced protection for a particular MTU,and is a function of the following: strength of core tech boundaries,strength of planned uses boundaries, strength of alternate usesboundaries, strength of other's uses boundaries, and even distributionof boundary strength.

A portfolio valuation tool for valuing an MTU of an improved computerfor technology determines balance scores for existing patents andforecasted future patents, and provides those scores to MTU how wellpatent protected co-processor 1692, which generates an overall balancescore and uses that overall balance score to determine how wellprotection provided by a patent portfolio (including existing patentsand/or forecasted future patents) is balanced across multiple MTUboundaries. A higher overall balance score indicates a higher degree ofbalanced protection for MTU boundaries.

A portfolio valuation tool includes portfolio factors score for existingpatents unit 1702 and portfolio factor score for forecasted futurepatents unit 1704. Portfolio factors score for existing patents unit1702 includes balance score unit 1716, and portfolio factor score forforecasted future patents unit 1704 includes balance score unit 1718.

Balance score unit 1716 generates a previous generation (PG) balancescore indicating how well protection provided by a portfolio of existingpatents is balanced across multiple MTU boundaries of a previousgeneration (PG) MTU. Balance score unit 1716 also generates a currentgeneration (CG) balance score indicating how well protection provided bya portfolio of existing patents is balanced across multiple MTUboundaries of a current generation (CG) MTU. The two scores are combinedto generate a total existing patents balance score by using a weightingfactor of CG to PG based on a disruption of CG MTU, a level ofinnovation of the CG MTU, or the like. In at least one embodiment, themore disruptive and innovative the CG technology is, the greater theweight assigned to the CG relative to the PG.

The balance score unit 1718 generates a remaining CG score indicatinghow well protection provided by a portfolio of forecasted future patentsis balanced across multiple MTU boundaries of a forecasted remaininglife of the CG MTU. Balance score unit 1718 also generates a nextgeneration (NG) balance score indicating how well protection provided bya portfolio of forecasted future patents is balanced across multiple MTUboundaries of a next generation (NG) MTU. Balance score unit 1718combines the two scores to generate a forecasted future balance score byusing a weighting factor of remaining CG balance to NG balance based ona disruption of the CG MTU and a level of innovation of the CG MTU, orthe like. In at least one embodiment, the more disruptive and innovativethe CG technology is, the greater the weight assigned to the NG relativeto the remaining CG.

Referring next to FIG. 330 another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology will be discussed. In particular, data used for generating aprevious generation balance score by portfolio factors score forexisting patents unit 1702 (FIG. 329 ) is illustrated. A score for eachprevious generation balance topic can be determined or obtained byPortfolio Factors Score for existing patents unit 1702.

In at least some embodiments, a score is generated for the followingprevious generation balance topics: MTU offered in products in PG, MTUcore tech well protected, MTU planned uses well protected, MTU extendedcore tech well protected, MTU extended core tech uses well protected,MTU alternate uses well protected, MTU extended uses well protected, MTUuses by targeted other well protected, and protection well balanced. Theprevious generation (PG) balance score is generated based on theindividual topic scores. The score for each topic represents a degree towhich each of the previous generation balance topics has been achieved.A higher overall previous generation score indicates that protectionprovided by a portfolio of existing patents is balanced across multipleMTU boundaries of a previous generation (PG) MTU. It should beappreciated that the illustrated topics are not an exhaustive list oftopics that may be scored by various embodiments.

Scores can be generated automatically, based on one or more of thefollowing: textual analysis of the documents; comparison of documents tosamples; comparison of scores assigned to other previous generationMTUs, human analysis/user provided input; automated computer analysisand score generation such as through the use of trained artificialintelligence (AI) bots, or some combination thereof.

In at least one such embodiment, if no MTU is offered in a previousgeneration product, the total previous generation score will be 0. If anMTU is offered in a previous generation product, the range for eachfunction is 0.0 to 0.1. If the MTU cannot be extended (e.g. the MTU isfully extended already), the maximum score will be assigned for topicsrelated to MTU extension. Similarly, if there are no alternatives orstandards related to the MTU, the maximum score will be assigned fortopics related to MTU alternatives or standards.

The previous generation balance score can be generated by summing thescores determined for one or more previous generation balance topics byaveraging topic scores, by determining a median topic score, or byperforming another suitable statistical analysis. In some embodiments,the previous generation balance score itself ranges from 0.0 to 0.1,while in other embodiments, the previous generation balance score can beas large as the sum of all individual topic scores. In some embodiments,any or all of the individual topic scores can be weighted relative toother topic scores so that adding the weighted individual topic scoresproduces a sum between 0.0 and 0.1. If the protection well balancedscore is zero, the total PG balance score will also be 0.

Referring next to FIG. 331 another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology will be discussed. In particular, data used for generating acurrent generation balance score by portfolio factors score for existingpatents unit 1702 (FIG. 329 ) or a remaining current generation balancescore by portfolio factors score for forecasted future patents unit 1704(FIG. 329 ), is illustrated. A score for each CG (or remaining CG)balance topic can be determined or obtained by Portfolio Factors Scorefor existing patents unit 1702 and/or portfolio factors score forforecasted future patents unit 1704.

In at least some embodiments, a score is generated for the followingcurrent generation balance topics: MTU core tech well protected, MTUplanned uses well protected, MTU extended core tech well protected, MTUextended core tech uses well protected, MTU alternate uses wellprotected, MTU extended uses well protected, MTU uses by targeted otherwell protected, and protection well balanced. The current generation(CG) and remaining CG balance scores are generated based on theindividual balance topic scores. Note that in some embodiments, a singleCG balance score can be calculated, and split between CG and remainingCG based on a phase of the CG MTU. Thus, if the CG MTU has a lifeexpectancy of 3 years, and this analysis is being performed 1.5 yearsinto the life of the MTU, ½ of the single CG score can be assigned asthe CG score, while the remaining ½ of the CG score can be assigned asthe remaining CG score. Other suitable divisions are within the spiritand scope of this disclosure.

The score for each CG balance topic represents a degree to which each ofthe CG balance topics has been achieved. A higher overall CG balancescore indicates that protection provided by a portfolio of existingand/or forecasted future patents is balanced across multiple MTUboundaries of a current generation (CG) MTU. It should be appreciatedthat the illustrated topics are not an exhaustive list of topics thatmay be scored by various embodiments.

Scores can be generated automatically, based on one or more of thefollowing: textual analysis of the documents; comparison of documents tosamples; comparison of scores assigned to other previous generationMTUs, human analysis/user provided input; automated computer analysisand score generation such as through the use of trained artificialintelligence (AI) bots, or some combination thereof.

The range of scores for each balance topic is 0.0 to 0.1. If the MTUcannot be extended (e.g. the MTU is fully extended already), the maximumscore will be assigned for topics related to MTU extension. Similarly,if there are no alternatives or standards related to the MTU, themaximum score will be assigned for topics related to MTU alternatives orstandards.

The overall CG balance score can be generated by summing the scoresdetermined for one or more current generation (CG) topics, by averagingthose scores, by determining a median score, or by performing anotherstatistical analysis. In some embodiments, the overall CG score itselfranges from 0.0 to 0.1, while in other embodiments, the overall CG scoreis the sum of all individual topic scores. In some embodiments, any orall of the individual topic scores can be weighted relative to othertopic scores so that adding the weighted individual topic scoresproduces a sum between 0.0 and 0.1. If the protection well balancedscore is zero, the total CG balance score will also be 0.

Referring next to FIG. 332 another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology will be discussed. In particular, data used for generating anext generation (NG) balance score by portfolio factors score forforecasted future patents unit 1704 (FIG. 329 ), is illustrated. A scorefor each next generation (NG) balance topic can be determined orobtained by balance score unit 1718 included in portfolio factors scorefor forecasted future patents unit 1704.

In at least some embodiments, a score is generated for the following NGtopics: NG started, MTU core tech well protected, MTU planned uses wellprotected, MTU extended core tech well protected, MTU extended core techuses well protected, MTU alternate uses well protected, MTU extendeduses well protected, MTU uses by targeted other well protected, andprotection well balanced. The total NG balance score is generated basedon the individual topic scores.

The score for each NG balance topic represents a degree to which each ofthe NG topics has been achieved. A higher overall NG score indicatesthat protection provided by a portfolio of forecasted future patents isbalanced across multiple MTU boundaries of a next generation (NG) MTU.It should be appreciated that the illustrated topics are not anexhaustive list of topics that may be scored by various embodiments.

Scores can be generated automatically, based on one or more of thefollowing: textual analysis of the documents; comparison of documents tosamples; comparison of scores assigned to other previous generationMTUs, human analysis/user provided input; automated computer analysisand score generation such as through the use of trained artificialintelligence (AI) bots, or some combination thereof.

The range of balance scores for each function is 0.0 to 0.1. If the NGhas not yet started, the total NG balance score will be set to 0. If theMTU cannot be extended (e.g. the MTU is fully extended already), themaximum score will be assigned for topics related to MTU extension.Similarly, if there are no alternatives or standards related to the MTU,the maximum score will be assigned for topics related to MTUalternatives or standards.

The total NG balance score can be generated by summing the scoresdetermined for one or more next generation topics, by averaging thosescores, by determining a median score, or by performing anotherstatistical analysis. In some embodiments, the total NG balance scoreitself ranges from 0.0 to 0.1, while in other embodiments, the total NGscore is the sum of all individual topic scores. In some embodiments,any or all of the individual balance topic scores can be weightedrelative to other balance topic scores so that adding the weightedindividual topic scores produces a sum between 0.0 and 0.1. If theprotection well balanced score is zero, the total NG balance score willalso be 0.

Referring next to FIGS. 333 through 335 another embodiment of aportfolio factor score for existing patents unit and a portfolio factorscore for forecasted future patents units of a portfolio valuation toolfor valuing an MTU of an improved computer for technology will bediscussed. A pending to issued ratio score, sometimes referred to hereinas simply a pending to issued score, is one of the inputs used todetermine a portfolio factors score (FIG. 312 ). In various embodiments,the pending to issued ratio score is a function of the ratio of thenumber of pending applications divided by the sum of the number ofpending applications+ the number of issued patents.

As illustrated by FIG. 334 , portfolio factors score for existingpatents unit 1702 includes existing pending to issued score unit 1720,which calculates a pending to issued score for existing patents andapplications. Existing pending to issued score unit 1720 obtains data tobe used in generating a pending to issued score table or other datastructure from one or more data sources. Obtaining the data can includeone or more of issuing a query to a commercial, government, or specialtydatabase, performing data scanning and optical character recognition,receiving updated information periodically or in response to atriggering event. For example, one or more co-processors of an improvedcomputer system can be programmed to periodically query a patent-relateddatabase. If a query of that database indicates that a patentapplication in a portfolio has issued, automatic transfer of informationindicating the patent issuance can be transmitted to portfolio factorsscore for existing patents unit 1702. In at least one embodiment, thedata obtained for the issued patent score table is grouped into one ormore time periods. The time periods can be, for example, a year, aquarter, a month, a number of years, number of quarters, number ofmonths, or the like.

The time period can be determined in advance, and updated data can beobtained automatically one or more times each time period. In someembodiments, the time period can be specified by information included ina user query, or otherwise.

For a particular time period, issued existing patent score unit 1706sums the number of issued patents present in a portfolio over that timeperiod, sums the number of patents issued during that time period, sumsthe number of pending applications filed over that time period,calculates a pending to issued ratio, and calculates a pending to issuedscore. The process repeats until all data, summations, and calculationsfor all desired time periods have been processed.

As illustrated by FIG. 335 , portfolio factors score for forecastedfuture patents unit 1704 includes future pending to issued score unit1722, which calculates a pending to issued score for forecasted futurepatents and applications. Future pending to issued score unit 1722obtains data to be used in generating a pending to issued score table orother data structure from one or more data sources. Obtaining the datacan include one or more of issuing a query to a commercial, government,or specialty database, performing data scanning and optical characterrecognition, receiving updated information periodically or in responseto a triggering event, extrapolating existing patent data values, or thelike. In at least one embodiment, the data obtained for the pending toissued patent score table is grouped into one or more time periods. Thetime periods can be, for example, a year, a quarter, a month, a numberof years, number of quarters, number of months, or the like.

The time period can be determined in advance, and updated data can beobtained automatically one or more times each time period. In someembodiments, the time period can be specified by information included ina user query, or otherwise.

For a particular time period, issued future pending to issued score unit1722 sums the number of patents forecast to be issued over that timeperiod, sums the number of pending applications forecast to be filedover that time period, calculates a forecast pending to issued ratio,and calculates a forecast pending to issued score. The process repeatsuntil all data, summations, and calculations for all desired timeperiods have been processed.

Referring next to FIG. 336 another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology will be discussed. In particular, data used by portfoliofactors score for existing patents unit 1702 (FIG. 334 ) to determine apending to issued portfolio factor score is discussed.

In various embodiments, the data obtained by portfolio factors score forexisting patents unit 1702 (FIG. 334 ) includes data used to form datarecords for existing time period(s) that have been completed (e.g.previous year(s)), a current time period (CP) that has not yet beencompleted (e.g. the current year), and some number of “next periods”(NPs) (e.g. the next 7 years). In some embodiments the existing timeperiod(s), current time period, and next time periods need not be of thesame duration. Thus, the existing time period can be the past 10 years,while the current time period can be 1 year, and the next time periodscan have varying durations of between about 2-5 years.

The data obtained by portfolio factors score for existing patents unit1702 includes, but is not limited to, at least one of the following:number of issued patents, number of pending applications, a pending toissued percentage, and a pending to issued score. As illustrated, eachrow of data in the pending to issued score table includes informationlinked to a particular period of time (e.g. existing, CP, 1 st-7^(th)NP). The information in the rows can be organized and stored as a recordwithin a database. For example the illustrated table (or some other datastructure) can be stored within, or linked to, an MTU record. Similarly,some or all of the information can be individually stored, or stored inother records linked to each other using relational database linkingtechniques. Note that the data used by portfolio factors score forexisting patents unit 1702 can use forecasted data, despite the factthat the data is used by existing patents unit 1702.

Referring next to FIG. 337 another example of calculated data for aportfolio factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology will be discussed. In particular, data used by portfoliofactors score for forecasted future patents unit 1704 (FIG. 335 ) todetermine a forecast pending to forecast issued portfolio factor scoreis discussed.

In various embodiments, the data obtained by portfolio factors score forforecasted future patents unit 1704 (FIG. 335 ) includes data used toform data records for existing time period(s), a current time period(CP) that has not yet been completed (e.g. the current year), and somenumber of “next periods” (NPs) (e.g. the next 7 years). In someembodiments the time periods need not be of the same duration.

The data obtained by portfolio factors score for forecasted futurepatents unit 1704 includes, but is not limited to, at least one of thefollowing: number of issued patents, number of pending applications, apending to issued percentage, and a pending to issued score.

As illustrated, each row of data in the pending to issued score tableincludes information linked to a particular period of time (e.g.forecasted future, CP, 1^(st)-7^(th) NP). The information in the rowscan be organized and stored as a record within a database. For examplethe illustrated table (or some other data structure) can be storedwithin, or linked to, an MTU record. Similarly, some or all of theinformation can be individually stored, or stored in other recordslinked to each other using relational database linking techniques. Bycontrast with the data obtained by portfolio factors score for existingpatents unit 1702(FIG. 334 ), data obtained by portfolio factors scorefor forecasted future patents unit 1704 (FIG. 335 ) does not include anexisting number of issued patents or an existing number of pendingapplications, although the issued patent percentage and the issuedpatent score for an existing portfolio may be included.

Referring next to FIG. 338 a graph of pending to issued percentage vs.pending to issued score for valuing an MTU of an improved computer fortechnology will be discussed. The horizontal axis of the graphrepresents a pending to issued percentage for a portfolio with respectto an MTU. The vertical axis represents pending to issued score for thesame portfolio with respect to the same MTU. In at least one embodiment,the pending to issued percentage equals the number of issued patentsdivided by the number of pending applications.

In various embodiments, two different S-Curve equations are used fordifferent portions of the graph. In at least one such embodiment, whenthe pending to issued percentage is greater than or equal to 50%, afirst S-Curve equation is used to generate values from 1.0 to 0.1 as thepending to issued percentage increases. But when the pending to issuedpercentage is less than 50%, a second S-Curve equation is used togenerate values from 0.5 to 1.0 as the pending to issued percentageincreases.

An S-Curve function, sometimes referred to as a sigmoid function, cantake many different forms. A basic sigmoid function is represented bythe following equation: S(x)=1/(1+e{circumflex over ( )}((f(x)).S-curves having varying characteristics can be achieved by varying f(x)in the exponent, adding constants, or the like. For any particular Scurve function (S(x)) the value of the invention scope score isdetermined by the actual to ideal percentage.

Referring next to FIG. 339 an embodiment of an invention scope factorscore for existing patents unit and an invention factor score forforecasted future patents units of a portfolio valuation tool forvaluing an MTU of an improved computer for technology will be discussed.Invention scope factor score for existing patents unit 1730 determinesan existing invention scope factors score based on the actual andtargeted number of inventions (actual number of inventions+ targetednumber of inventions) protected by existing patents. Similarly,invention scope factor score for forecasted future patents unit 1732determines a forecasted future invention scope factors score based onthe actual and targeted number of inventions (actual number ofinventions+ targeted number of inventions) forecast to be protected byfuture patents divided by an ideal number of inventions protected.

Both the existing invention scope factors score and the forecastedfuture invention scope factors score are determined on a period byperiod basis. Thus, the scope factor scores can be determined in aquarterly basis, a yearly basis, a technology cycle basis, or the like.

In various embodiments, the portfolio valuation tool combines the actualand targeted number of existing inventions protected with the actual andtargeted number of inventions forecast to be protected by future patentsprotected by existing patents to generate a combined actual and targetednumber of inventions protected. The ideal number of inventions used byboth Invention scope factor score for existing patents unit 1730 andinvention scope factor score for forecasted future patents unit 1732can, but need not be the same. Furthermore, the ideal number ofinventions protected may vary based on the time period being considered.For example, it may be ideal to protect a large number of inventionsearly on, and add lesser numbers of protected inventions later.Consequently, the ideal number of inventions protected during anyparticular period may be greater or less than the ideal number protectedin a previous or later period. However, in some embodiments the numberof protected inventions is cumulative, and will generally increase overtime.

The total invention scope factors score is a function of the combinedactual and targeted number of inventions protected divided by thecombined idea number of inventions protected.

Referring next to FIGS. 340 through 342 another embodiment of aninvention scope factors score for existing patents unit and an inventionfactors score for forecasted future patents units of a portfoliovaluation tool for valuing an MTU of an improved computer for technologywill be discussed. In at least one embodiment, the actual and targetednumber of inventions protected, which is used in determining theinvention scope factors score, is equal to the product of a targetpercentage and the ideal number of inventions added to the actual numberof inventions protected prior to the current period.

Invention scope factors score for existing patents unit 1730 (FIG. 341 )includes existing actual invention protected unit 1734, which obtainsthe existing total of inventions actually protected, obtains theexisting total of ideal number of inventions to protect, calculates anactual to ideal percentage, and applies the actual to ideal percentageto an S-curve function to obtain an existing invention scope score.Obtaining the existing total of inventions actually protected and theexisting total of ideal number of inventions to protect can includeretrieving data from a data structure (e.g. one or more databases ortables), receiving user input, scraping data from one or more websites,accessing one or more public information repositories, extractinginformation from textual documents, or the like. Applying the actual toideal percentage to an S-curve function to obtain an existing inventionscope score is discussed further with reference to FIG. 344 .

Invention factors score for forecasted future patents units 1732(FIG.342 ) includes future actual invention protected unit 1736, whichobtains data for inclusion in an actual to ideal score table. Obtainingthe data can include one or more of issuing a query to a commercial,government, or specialty database, performing data scanning and opticalcharacter recognition, and/or receiving updated information periodicallyor in response to a triggering event, receiving user input, scrapingdata from one or more websites, or the like.

For a given period of time, future actual invention protected unit 1736calculates and actual to ideal percentage, and applies the actual toideal percentage to an S-curve function to obtain an existing inventionscope score. The process performed by future actual invention protectedunit 1736 continues until existing invention scope scores are determinedfor each time period of interest. Applying the actual to idealpercentage to an S-curve function to obtain an existing invention scopescore is discussed further with reference to FIG. 344 .

Referring next to FIG. 343 of an example of calculated data for aninvention factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology will be discussed. In particular, the calculated data isstored in an actual to ideal score table that can be used by InventionScope Factors Score for existing patents unit 1730 (FIG. 341 ) andInvention Scope Factors Score for future patents unit 1732 (FIG. 342 )to calculate an actual to ideal percentage, or score.

In various embodiments, the data in the actual to ideal score tableincludes data used to form data records for a current time period (CP)that has not yet been completed (e.g. the current fiscal quarter), andsome number of “next periods” (NPs) (e.g. the next 7 fiscal quarters).In some embodiments the time periods need not be of the same duration.The data stored in the actual to ideal score table includes, but is notlimited to, at least one of the following: targeted number of inventionsper period, running total of targeted inventions per period, idealnumber of inventions per period, running total of ideal inventions perperiod, actual to ideal percentages per period, and invention scopescores per period.

As illustrated, each row of data in the pending to issued score tableincludes information linked to a particular period of time (e.g.forecasted future, CP, 1 ^(st)-7 ^(th) NP). The information in the rowscan be organized and stored as a record within a database. For examplethe illustrated table (or some other data structure) can be storedwithin, or linked to, an MTU record. Similarly, some or all of theinformation can be individually stored, or stored in other recordslinked using relational database linking techniques.

Referring next to FIG. 344 a graph of a score to actual to idealinvention percentage for valuing an MTU of an improved computer fortechnology will be discussed. The Y axis of graph represents theinventions scope score, and the X axis represents the actual to idealpercentage. The function represented by the curve is an S-Curvefunction, sometimes referred to as a sigmoid function with a minimumvertical offset.

Referring next to FIG. 345 another embodiment of an invention scopefactor score for existing patents unit and an invention factor score forforecasted future patents units of a portfolio valuation tool forvaluing an MTU of an improved computer for technology will be discussed.

Invention scope factor score for existing patents unit 1730 includesideal number of existing inventions protected unit 1738, whichdetermines an ideal number of inventions protected by existing patentsby multiplying a previous generation (PG) scale factor by a PG idealnumber of inventions, and adding that product to a current generation(CG) ideal number of inventions and to a next generation (NG) idealnumber of inventions. The result of this calculation is then multipliedby a competitor scale factor to arrive at the ideal number of existinginventions protected.

Similarly, invention scope factor score for forecasted future patentsunit 1732 includes ideal number of future inventions protected unit1740, which determines an ideal number of inventions protected by futurepatents by multiplying a previous generation (PG) scale factor by a PGideal number of inventions, and adding that product to a currentgeneration (CG) ideal number of inventions and to a next generation (NG)ideal number of inventions. The result of this calculation is thenmultiplied by a competitor scale factor to arrive at the ideal number offuture inventions protected.

In various embodiments, the portfolio valuation tool combines theexisting PG scale factor, the existing PG ideal number of inventions,the existing CG ideal number of inventions, and the existing NG idealnumber of inventions to the forecasted future PG ideal number ofinventions, the forecasted future CG ideal number of inventions, and theforecasted future NG ideal number of inventions to generate a combinedideal number of inventions protected.

Referring next to FIGS. 346 and 347 another embodiment of an inventionscope factor score for existing patents unit and an invention factorscore for forecasted future patents units of a portfolio valuation toolfor valuing an MTU of an improved computer for technology will bediscussed. In at least one embodiment, the competitor scale factor,which is used in determining the ideal number of inventions protected,is equal to a function of ownership percentage of the number ofinventions identified, patent proficiency, financial strength, andpatent aggressiveness.

Competitor scale factor unit 1742 (FIG. 347 ) obtains data to beincluded in a data table for top “x” competitors. For each competitor,competitor scale factor unit 1742 calculates an invention percentagescore a proficiency score, a financial score, an aggression score, andcompetitor score. These computations are repeated until values arecalculated for each of the top “x” competitors. After competitorcomputations have been completed, competitor scale factor unit 1742calculates a competitor scale factor from the competitor scores. In atleast one embodiment, Ideal number of future Inventions Protected unit1740 and Ideal number of existing Inventions Protected unit 1738 share asingle competitor scale factor unit.

In various embodiments, the proficiency score is a function of portfoliosize. For example, a competitor with a large portfolio is likely to bemore proficient at using the patent process to protect inventions ascompared to a competitor with a smaller portfolio. The aggression scoreis a function of active licensing and litigation activity. For example,a competitor who actively licenses their patent portfolio and is notafraid to initiate patent litigation is considered more aggressive thana competitor who does not license or enforce their portfolio. Thefinancial score is a function of market capitalization and profits.

Referring next to FIG. 348 another example of calculated data for aninvention factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology will be discussed. A competitor data table or other datastructure includes records for individual competitors, and can bepopulated with data by competitor scale factor unit 1742. Eachcompetitor record can include data on the percentage of MTU inventionsprotected by the competitors portfolio, the size of the competitorsportfolio, the competitors market capitalization, financial reportinformation, and a number of patents that have been licensed orlitigated.

Although only a single competitor is illustrated in the competitor datatable, any number of competitors can be included. Furthermore, variousembodiments of the competitor data table can include additional or lessinformation. In some embodiments, the competitor data table can begenerated as-needed from information stored in disparate databases.

Referring next to FIG. 349 another example of calculated data for aninvention factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology will be discussed. The competitor scoring table (FIG. 349 )is used in conjunction with the competitor data table (FIG. 348 ) todetermine a competitor score for each individual competitor. The dataincluded in the competitor scoring table includes columns for an itemscore coefficient, a percentage of MTU inventions protected level, anumber of patents level, a market capitalization level, a financialscore level, and a licensing and litigation level. A weighting value isassigned to each of the columns, except the item score column.

Each row of the competitor scoring table is organized to associate anitem score with a level from each of the columns. For example, itemscore 1 is associated with a 1% of MTU inventions protected level, a 100number of patents level, a $50 million dollar market capitalizationlevel, a −$50 million dollar financial level, and a 2 licensing andlitigation level. The remaining item scores are similarly associatedwith each of the different levels.

To generate a competitor score, the data for a competitor included ineach column of the competitor data table is compared to the values incorresponding columns of the competitor scoring table, and assigned anitem score corresponding to the closest value in the competitor scoringtable. Taking competitor one as an example, consider the following. The% of MTU inventions protected in competitor data table rounds up to 8%in the competitor scoring table, so competitor one will receive an itemscore of 3 for % of MTU inventions protected. Similarly, competitorone's portfolio size of 427 rounds up to 500 in the competitor scoringtable's “all patents” column, so competitor one receives an item scoreof 2 for portfolio size. A market capitalization of 2,500 rounds up to10,000, so competitor one receives an item score of 4 for marketcapitalization. A financial report indicating+47 rounds up to 50, socompetitor one receives an item score of 3 for financials. A licensingand litigation value of 2 matches a licensing and litigation level of 2,so competitor one receives an item score of 2 for licensing andlitigation.

In various embodiments, rather than rounding up values in the competitordata table to determine corresponding item scores, values can be roundedto the nearest level. For example, a market capitalization of 2,500 iscloser to the 2,000 level of the competitor scoring table, so competitorwould be assigned an item score of 3 in such an embodiment.Additionally, different weighting factors can be used. Weighting factorscan, but need not be, determined empirically based on historical, usingstatistical distributions, or some combination thereof.

Referring next to FIG. 350 another example of calculated data for aninvention factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology will be discussed. A competitor score determination tableillustrates data sued to determine a competitor score for a particularcompetitor. The following example continues with the example used inFIGS. 348 and 349.

Competitor 1, which has % of MTU inventions protected value of 6.2%(FIG. 348 ), receives an item score of 3 for % of MTU inventionsprotected (FIG. 349 ). The competitor scoring table indicates that aweighting factor of 2.25 is assigned to assigned to % of MTU inventionsprotected. Competitor score determination table, therefore, shows thatcompetitor one's % of MTU inventions protected score equals the itemscore (δ) multiplied by the weighting factor (2.25), which yields aresult of 6.75. Scores for each of the percentage of MTU inventionsprotected by the competitors portfolio, the size of the competitorsportfolio, the competitors market capitalization, financial reportinformation, and a number of patents that have been licensed orlitigated by multiplying the item scores by weighting factors associatedwith each data type. Thus, competitor one will have a portfolio sizescore of 3 (2*1.5), a market cap score of 6 (4*1.5), a financial reportscore of 4.5 (3*1.5), and a licensing and litigation score of 0.75(1*0.75). These scores are added together to generate the competitorscore, which in this example is 21.

Referring next to FIGS. 351 and 352 another embodiment of an inventionscope factor score for existing patents unit and an invention factorscore for forecasted future patents units of a portfolio valuation toolfor valuing an MTU of an improved computer for technology will bediscussed. In various embodiments herein, the degree to which previousgeneration (PG) technology effect current generation (CG) technology canimpact forecasts regarding the number of patents needed to protect anMTU, how quickly the value of the MTU will change, and how quickly thecompetitive landscape is likely to change, among other things.

A PG scale factor can be used as an indicator of how much PG technologyeffects CG technology. In various embodiments, the PG scale factor is afunction of PG level of disruption, CG level of disruption, and thedegree to which CG technology will be in competition with PG technology.

Previous generation (PG) scale factor unit 1743 determines a PG scalefactor by determining a PG disruption level, determining a CG disruptionlevel, determining an initial PG to CG score based on disruption curve,and adjusting the initial PG to CG score if an MTU is used in PGproducts. In various embodiments, a single PG scale factor unit 1743 isfor both ideal number of future inventions protected unit 1740 and idealnumber of existing inventions protected unit 1738.

The PG disruption level and the CG disruption level can be determinedbased on analysis of MSBTP (marketing, sales, business, technology, andpatent) data (e.g. FIGS. 24-26 ), and can be automatically adjusted asmore data is ingested. Using the disruption curve to determine the PG toCG score will be discussed subsequently with respect to FIG. 353 . Theamount by which the initial PG to CG score is adjusted is based on levelof use of the MTU in the PG technology, and which curve is used.Adjusting the initial PG to CG score if an MTU is used in PG productswill be further discussed with reference to FIG. 353 .

Referring next to FIG. 353 a graph of PG to CG score to CG level ofdisruption for valuing an MTU of an improved computer for technologywill be discussed. The illustrated curves are sometimes referred toherein as disruption curves, and the graph will be referred to as adisruption graph. There are 4 disruption curves on the illustrateddisruption graph: a PG REV curve, used for previous generation techassigned a revolutionary status; a PG EVO curve, used for previousgeneration tech assigned an evolutionary status; a PG BMT curve, usedfor previous generation tech assigned a “better mousetrap” status; and aPG INC curve, used for previous generation tech assigned an incrementalstatus. Each of the different curves is generated based on dataanalysis, and continually evolves as new data becomes available.

As used herein, an incremental status is assigned to PG technology thatprovides a near imperceivably better way of doing things and/or slightlyreduces market share of predecessors. A better mousetrap status isassigned to PG technology that provides a more easily perceivably betterway of doing things and/or plainly reduces market share of predecessors.An evolutionary status is assigned to PG technology that obsoletes manypredecessors and/or expands market opportunities. A revolutionary statusis assigned to PG technology that obsoletes predecessors, expandsmarkets, and/or opens new market opportunities.

To determine an initial PG to CG score, the PG disruption level is usedto select an appropriate disruption curve. In the illustrated example,the PG EVO curve is selected because the PG disruption level isdetermined to be evolutionary. The initial position on the selectedcurve is determined based on the CG level of disruption. In theillustrated example, the CG level of disruption is approximately 25%, sothe initial position on the PG EVO curve is shown as a square atlocation (1), which corresponds to a PG to CG score of about 0.35.

If the MTU being evaluated is used in the PG technology, then the PG toCG score is increased by sliding the initial position on the PG EVOcurve left to location (2), which corresponds to a PG to CG score ofabout 0.42. Sliding the point left on a curve has the same effect asdecreasing the CG level of disruption. The amount by which the initialposition is adjusted can vary based on a degree to which the MTU is usedin the PG technology, with heavy use resulting in moving the point agreater distance along the curve. In some embodiments, amount ofmovement is a set amount, regardless of how heavily the MTU isincorporated into the PG technology.

Referring next to FIGS. 354 and 355 another embodiment of an idealnumber of inventions unit of an invention scope factor score forexisting patents unit and of an invention factor score for forecastedfuture patents units of a portfolio valuation tool for valuing an MTU ofan improved computer for technology will be discussed. Ideal number ofinventions unit 1744 generates MTU to inventive embodiment mapping (FIG.360 ) and calculates generation time frames (FIG. 356 ).

A determination is made whether the current generation MTU has aprevious generation (PG), and whether the MTU has a next generation(NG). If it is determined that the MTU has only A PG and CG (i.e. PGyes, NG no) the method proceeds to off-page reference A on FIG. 355 ,which will be discussed subsequently. If it is determined that the MTUhas all three generations, i.e. a PG, CG, and NG (PG yes, NG yes), themethod proceeds to off-page reference B on FIG. 355 .

If the MTU has only a CG (PG no, NG no), ideal number of inventions unit1744 tabulates inventive embodiments as CG TNI, meaning that the numberof invention in the current generation is the total number of inventions(TNI), can calculates the ideal number of inventions (INI) from thenumber of current generation inventions, which is also the TNI.

If the MTU has only a CG and an NG (PG no, NG yes), a determination ismade whether the next generation (NG) has started. In at least oneembodiment, this determination is made based, at least in part on thegeneration timeframes previously calculated.

If the NG has started, ideal number of inventions unit 1744 tabulates afirst portion of existing inventive embodiments as a first quantity ofCG TNI, and tabulates a second portion of existing inventive embodimentsas a first quantity of NG TNI. Ideal number of inventions unit 1744 alsotabulates a first portion of forecasted inventive embodiments as asecond quantity of CG TNI and tabulates a second portion of forecastedinventive embodiments as a second quantity of NG TNI.

Ideal number of inventions unit 1744 then sums the first quantity of CGTNI and the second quantity of CG TNI to determine a calculated CG TNI.The ideal number of current generation inventions (CG INI) is thendetermined from the calculated total number of current generationinventions (CG TNI). Similarly, ideal number of inventions unit 1744sums the first quantity of NG TNI and the second quantity of NG TNI todetermine a calculated NG TNI. The ideal number of next generationinventions (NG INI) is then calculated from the calculated total numberof next generation inventions (NG TNI).

If the NG has not started, ideal number of inventions unit 1744tabulates existing inventive embodiments as a first quantity of CG TNI,and tabulates a first portion of forecasted inventive embodiments as asecond quantity of CG TNI. Ideal number of inventions unit 1744 thensums the first quantity of CG TNI and the second quantity of CG TNI todetermine a calculated CG TNI. The ideal number of current generationinventions (CG INI) is then determined from the calculated total numberof current generation inventions (CG TNI).

Ideal number of inventions unit 1744 also tabulates a second portion offorecasted inventive embodiments as NG TNI, and tabulates a secondportion of existing inventive embodiments as a second quantity of CGTNI. The ideal number of next generation inventions (NG INI) is thendetermined from the calculated total number of next generationinventions (NG TNI).

Referring next to off-page reference A of FIG. 355 , the functionsperformed in response to ideal number of inventions unit 1744determining that the MTU has only a PG and CG will be discussed. Asillustrated by block 1750 ideal number of inventions unit 1744 tabulatesa first portion of existing inventive embodiments (IE) as a firstquantity of CG TNI. As illustrated by block 1752, ideal number ofinventions unit 1744 tabulates a second portion of existing inventiveembodiments (IE) as a first quantity of PG TNI.

As illustrated by block 1754 ideal number of inventions unit 1744tabulates a first portion of forecasted inventive embodiments (1E) as asecond quantity of CG TNI. As illustrated by block 1752, ideal number ofinventions unit 1744 tabulates a second portion of forecasted inventiveembodiments (IE) as a second quantity of PG TNI.

As illustrated by block 1758, ideal number of inventions unit 1744 sumsthe first quantity of CG TNI and the second quantity of CG TNI todetermine a calculated CG TNI. The ideal number of current generationinventions (CG INI) is then determined from the calculated total numberof current generation inventions (CG TNI).

As illustrated by block 1760, ideal number of inventions unit 1744 sumsthe first quantity of PG TNI and the second quantity of PG TNI todetermine a calculated PG TNI. The ideal number of previous generationinventions (PG INI) is then determined from the calculated total numberof previous generation inventions (PG TNI).

Referring next to off-page reference B of FIG. 355 , the functionsperformed in response to ideal number of inventions unit 1744determining that the MTU has all three of a PG, a CG, and an NG will bediscussed. As illustrated, ideal number of inventions unit 1744determines whether the NG has started. If the NG has not started, steps1750-1760 for existing inventive embodiments are performed. Ideal numberof inventions unit 1744 tabulates a first portion of forecastedinventive embodiments (IE) as a third quantity of CG TNI, and sums thefirst, second and third quantities of CG TNI to obtain a calculated CGTNI. Ideal number of inventions unit 1744 then calculates the idealnumber of inventions for the current generation (CG INI) from thecalculated CG TNI. Ideal number of inventions unit 1744 also tabulatesthe second portion of forecasted inventive embodiments to arrive at acalculated NG TNI. The ideal number of inventions for the nextgeneration (NG INI) are calculated from the calculated NG TNI.

If the NG has started, ideal number of inventions unit 1744 tabulates afirst portion of existing inventive embodiments (IE) to obtain the totalnumber of previous generation inventive embodiments (PG TNI), tabulatesa second portion of existing IE as a first quantity of CG TNI, andtabulates a third portion of existing IE as a first quantity of NG TNI.Ideal number of inventions unit 1744 also tabulates a first portion offorecasted IE as a second quantity of CG TNI, and tabulates a secondportion of forecasted IE as a second quantity of NG TNI.

Ideal number of inventions unit 1744 sums the first quantity of CG TNIand the second quantity of CG TNI to obtain a calculated CG TNI, whichused to further calculate the ideal number of inventions for the currentgeneration (CG INI). Similarly, ideal number of inventions unit 1744sums the first quantity of NG TNI and the second quantity of NG TNI toobtain a calculated NG TNI, which in turn is used to calculate the idealnumber of inventions for the next generation (NG INI).

Referring next to FIG. 356 an ideal number of inventions unit of aninvention scope factor score for existing patents unit and of aninvention factor score for forecasted future patents units of aportfolio valuation tool for valuing an MTU of an improved computer fortechnology will be discussed. Ideal number of inventions unit 1744,which can be included in either or both of an invention scope factorscore for existing patents unit and an invention factor score forforecasted future patents units of a portfolio valuation tool, includesa calculate generation time frames unit.

Calculate generation time frames unit determines generation time framesby comparing earlier unique value propositions (UVPs) with more recentUVPs. Calculate generation time frames unit determines whether adifference between one or more of the earlier and more recent UVPs isgreater than a first threshold value. If not, then the differencebetween the earlier UVPs and the more recent UVPs indicates that theMTUs are so similar that only one generation, the current generation,exists. If the difference between the earlier UVPs and the more recentUVPs is greater than the first threshold but less than the secondthreshold, two generations of the MTU (PG and CG) exist. If thedifference between the earlier UVPs and the more recent UVPs is greaterthan the second threshold, three generations of the MTU (PG, CG, and NG)exist. In at least some embodiments, the first threshold can bedetermined according to the equation y=n*x, where n is a constant, and xrepresents an original number of traits (or UVPs) associated with anMTU. In some embodiments the value of x can include a quality of thetraits can be taken into account in addition to a number of the traits.The second threshold can be determined according to the equation z=m*y,where m is a constant and y is the first threshold.

In various embodiments, the constants n and m are 2 or greater, so thatthe if the number of MTU traits (UVPs) doubles in comparison to theoriginal number of MTU traits, then the first threshold is satisfied.Similarly, if the number of MTU traits (UVPs) is 4 times the number oforiginal traits, or double the first threshold, the second threshold issatisfied. Either threshold can be adjusted based on data analysis ofvarious factors described herein, and the two constants need not beequal. For example a level of disruption, the rate at which new traitsare identified, competitive information, or the like can be used incombination with, or in place of, the UVP comparisons to aid thedetermination of generational time frames.

Referring next to FIG. 357 a graph of UVP traits to time for valuing anMTU of an improved computer for technology will be discussed. UVP traitsgraph illustrates the number of UVPs over time. During a previousgeneration, the number and/or quality of UVPs remains essentiallyconstant for a period of time designated as “PG”. The number and/orquality of UVPs increases to a point that the first threshold (y=n*x) issatisfied during the current generation (PG), and satisfies the secondthreshold (z=m*y) during a period of time designated as the nextgeneration (NG). In general, the increase in the number and/or qualityof the UVPs/traits can be used to identify generational changes in anMTU.

Referring next to FIG. 358 another embodiment of an ideal number ofinventions unit of an invention scope factor score for existing patentsunit and of an invention factor score for forecasted future patentsunits of a portfolio valuation tool for valuing an MTU of an improvedcomputer for technology will be discussed. Ideal number of inventionsunit 1744 partitions inventions among generations when two or moregenerations are determined to exist. As illustrated by FIG. 358 , idealnumber of inventions unit 1744 tabulates a first portion of existing IEsas a first quantity of CG TNI, and identifies the first portion ofexisting IEs as being associated with CG UVPs. Ideal number ofinventions unit 1744 also tabulates a second portion of existing IEs asa first quantity of NG TNI, and identifies the second portion ofexisting IEs as being associated with NG UVPs.

Ideal number of inventions unit 1744 tabulates a second portion offorecasted IEs as a second quantity of NG TNI, and identifies the secondportion of forecasted IEs as being associated with CG UVPs. Ideal numberof inventions unit 1744 tabulates a first portion of forecasted IEs as asecond quantity of CG TNI, and identifies the second portion offorecasted IEs as being associated with NG UVPs.

Referring next to FIG. 359 a graph of generations to time for valuing anMTU of an improved computer for technology will be discussed. Thegenerations graph illustrates how inventions are partitioned. Thegeneration is shown on the vertical axis, and the horizontal axisrepresents time. Gen “b” inventions, also referred to as currentgeneration (CG)

The “present” is demarcated from the “future” by the change from“existing” to “forecasted.” During the present period, there areexisting inventions from both the current generation of technology (genb) and the next generation of technology (gen b+1). During the futureperiod, inventions for both gen b and gen b+1 have been forecast. Invarious embodiments, determining which existing and forecast inventionsbelong to which generation of technology is necessary for properportfolio valuation.

The fact that an invention currently exists does not provide sufficientinformation to determine the generation to which the invention belongs.Similarly, a forecast invention can belong to gen b or gen b+1. Idealnumber of inventions unit 1744 uses the UVPs/traits of each particularinvention to determine whether a particular existing or forecastedinvention belongs to the current generation (gen b) or the nextgeneration (gen b+1).

Referring next to FIG. 360 an MTU to inventive embodiment mapping forvaluing an MTU of an improved computer for technology will be discussed.As previously discussed with respect to FIG. 354 , ideal number ofinventions unit 1744 performs MTU to inventive embodiment mapping. TheMTU to inventive embodiment mapping shows various factors that can beused to identify which MTU an inventive embodiment belongs to.

MTUs can be identified based on their characteristics. For example, MTU−0 includes particular UVPs and particular features, but not others. Ina very basic example, an electric motor does not have the same UVPs orfeatures as mobile phone. But a smart mobile phone will not have thesame UVPs or features as a flip phone, and so would not be included inthe MTU as the smart phone, even though they are similar in many ways.Each MTU will have its own tech challenges, problems, inventive conceptssolutions, and/or inventive embodiments. The greater the number of theseMTU factors a product possesses, the greater the likelihood that theproduct will be included in an MTU. In some embodiments to be assignedto a particular MTU, an inventive embodiment must have substantially allof these characteristics in common.

In at least one embodiment, an inventive embodiment can belong to morethan one MTU. For example, inventive embodiments included in MTU1-1 arealso included in MTU-1. Likewise, inventive embodiments included inMTU2-1 are also included in MTU-2. In some such embodiments, thecharacteristics of a sub-MTU are closely related, but not necessarilyidentical to the characteristics of a parent MTU. Thus, if MTU-2includes computer display screens, MTU-2-1 might include touch-screencomputer displays. In this example, a touch screen would havesubstantially similar characteristics to other computer display screens,but the touch screen displays would additional UVPs, features, techchallenges, problems, and the like.

Referring next to FIGS. 361 and 362 an embodiment of a market-patent “k”factor co-processor of a portfolio valuation tool for valuing an MTU ofan improved computer for technology will be discussed. Market-patent “k”factor co-processor 1656 includes a market differentiator based on techunit 1770, a patent competition unit 1772, and a patent need calculationunit 1774.

Market differentiator based on tech unit 1770 receives some or all ofthe following MTU related information: MTU sales reports, inclusion MTUsales reports, composition MTU sales reports, MTU marketing materials,inclusion MTU marketing materials, composition MTU marketing materials,MTU market reports, inclusion MTU market reports, composition MTU marketreports, MTU features, inclusion MTU features, composition MTU features,MTU tech challenges, inclusion MTU tech challenges, and composition MTUtech challenges. Market differentiator based on tech unit 1770 processesand distills the MTU information to generate one or more marketdifferentiation results, which provide an indication of how unique theMTU is compared to other products. In some embodiments, the one or moremarket differentiation results also include results indicating howimport technology is as a distinguishing feature in a particular market,a number of competitors, & size of competitors.

Patent competition unit 1772 receives some or all of the followinginformation: MTU features, inclusion MTU features, composition MTUfeatures, MTU tech challenges, inclusion MTU tech challenges andcomposition MTU tech challenges, MTU patent data, inclusion MTU patentdata, and composition MTU patent data. Patent competition unit 1772processes and distills the MTU information to generate one or morecompetition results, which provide an indication of how much competitionthe MTU faces.

The market differentiation result and the competition result areprovided to patent need calculation unit 1774, which uses them togenerate a “k” factor output. In at least one embodiment, the “k”factor=market leverage factor ((patent need v. level ofcompetition)*market opportunity driven by tech). The “k” factor is amarket-wide measure and is not competitor specific. The “k” factor graphillustrated in FIG. 362 shows how the “k” factor relates to patent needand technology competition.

FIGS. 363 and 364 are a diagram of an embodiment of patent use toolexecuted by co-processor of an improved computer for technology. FIG.363 illustrates the patent exploitation unit 256 of the improvedcomputer generating an MTU patent use data per patent holder report asshown in FIG. 364 . The unit 256 retrieves MSBT data and patent dataregarding one or more MTUs, which corresponds to an existing item and/ora new item.

From the retrieved data, the improved computer generates the use reportas shown in FIG. 364 . The report includes rows for each patent holderand columns for use data results. The columns include the field headersof patent holder ID, patent use tendencies, the name of an MTU, the lifedata of the MTU, patent position, market presence, use likelihood, anduse score. The patent holder ID column includes one or more fields perpatent holder for information regarding the patent holder (e.g., name,address, market cap, markets of interest, etc.). The patent usetendencies column includes one or more fields per patent holder for thepatent holders tendencies with respect to buying patents, sellingpatents, licensing patents, and/or litigating patents.

The life data for an MTU column includes one or more fields per patentholder for start date, end of life data, time frame of phases, and mayfurther include generational data. The patent position column includesone or more fields per patent holder for the patent position of thepatent holder ranging from weak to superior on a sliding scale basis.The market presence column includes one or more fields per patent holderregarding the patent holder's sales and/or product/service offerings ofexisting and/or new products/services that embody this MTU, one or moreinclusion MTUs, one or more composition MTUs, and/or one or more relatedMTUs. The use likelihood column includes one or more fields per patentholder for indicating how the patent holder will likely use the MTU. Theuse score column includes one or more fields per patent holder includesone or more fields for a use score which is a calculation of the otherdata elements to provide insight into the most beneficial uses of MTUand/or its patents.

FIG. 365 is a diagram of an embodiment of patent data extraction toolexecuted by co-processor of an improved computer for technology. Theco-processor extracts data from a plurality of patents (e.g., issued,pending, PCT, foreign, provisional, etc.) and categorizes the data of apatent into a general patent data section, a claim data section, and aspecification and figure section. As previously discussed, the improvedcomputer uses the patent data of a patent to determine one or more ofproblem set up, solution & novelty, technical description, benefit ofsolution, technical environment & use of invention, and patent lawinterpretation with respect to an MTU.

FIG. 366 is a diagram of an example of calculated data for a patentquality analysis tool executed by a co-processor of an improved computerfor technology. For a patent, the co-processor determines a value ofeach of the following factors: correlation of claim terms to figureterms; clarity of claim term definition, clarity of novelty nuggets,clarity of solution, clarity of problem, clarity of benefit, clarity ofinventive concept, uses of absolutes in claims (no use unless theabsolute is a novelty nugget), proper claim term connectivity, numberclaim formality issues (e.g., claim numbering, antecedent basis), andclarity of enablement.

Each of these factors is multiplied by a corresponding weighting factorto produce a plurality of weighted scores. The weighted scores arecombined to produce a patent quality score. For example, issues with theclaims typically have a higher weighting factor than clarity of problemand solution, since the claims define the patent protection. Significantissues with the claims creates a very low quality score.

FIG. 367 is a logic diagram of an example of a method for calculatingpatent quality as performed by executed by a co-processor of an improvedcomputer for technology. The method begins at step 1800 where theimproved computer identifies claim terms of a claim. A claim termincludes one or more words regarding a claim noun (e.g., an element, astep, an input, output, and/or some quantifiable thing), a claimdescriptor (e.g., a feature, a function, a description, an interaction,an operational limitation of a claim noun and/or the like), and/or aclaim relator (relationship of two or more claim nouns). A technicalterm includes one or more words that is regarding a technical aspect ofan MTU.

The method continues at step 1802 where the improved computer determineswhether the claim includes a claim noun. If not, the method continues atstep 1806 where the improved computer determines that this a significantissue with the claim. The method continues at step 1818 where theimproved computer calculates a claim score based on the significantissue. For example, a claim score ranges from 1 to 10, where 1 is a lowscore indicating low quality and 10 is a high score indicating highquality.

If the answer at step 1802 was yes, the method continues at step 1804where the improved computer determines whether a claim descriptor isassociated with the claim noun. If not, the method continues at step1808 where the improved computer determines whether the claim noun isself-describing (e.g., a resistor is self-describing, a circuit is not).If not, the method continues at step 1806.

If the answer at step 1804 or 1808 was yes, the method continues at step1810 where the improved computer determines whether the claim includesmore than one claim noun. If not, the method continues at step 1812where the improved computer whether the claim noun is clearly a noveltynugget. If not, the method continues at step 1806. If yes, the methodcontinues at step 1814 where the improved computer concludes that thereare no apparent issues with the claim. The method continues at step1818.

If the answer to step 1810 was yes, the method continues at step 1816where the improved computer determines whether there is claim relatorthat connects the claim noun to another claim noun. If not, the methodcontinues at step 1806. If yes, the method continues at step 1820 wherethe improved computer determines whether there are more claim nouns toprocess. If not, the method continues at step 1814.

If the answer to step 1820 was yes, the method continues at step 1822where the improved computer determines whether a claim descriptor isassociated with the claim noun. If not, the method continues at step1824 where the improved computer determines whether the claim noun isself-describing (e.g., a resistor is self-describing, a circuit is not).If not, the method continues at step 1806.

If the answer to step 1822 or 1824 was yes, the method continues at step1826 where the improved computer determines whether there is a claimrelator that connects this claim noun to another claim noun. If not, themethod continues at step 1806. If yes, the method continues at step1820.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, text, graphics, audio, etc. any of which may generally bereferred to as ‘data’).

As may be used herein, the terms “substantially” and “approximately”provide an industry-accepted tolerance for its corresponding term and/orrelativity between items. For some industries, an industry-acceptedtolerance is less than one percent and, for other industries, theindustry-accepted tolerance is 10 percent or more. Other examples ofindustry-accepted tolerance range from less than one percent to fiftypercent. Industry-accepted tolerances correspond to, but are not limitedto, component values, integrated circuit process variations, temperaturevariations, rise and fall times, thermal noise, dimensions, signalingerrors, dropped packets, temperatures, pressures, material compositions,and/or performance metrics.

Within an industry, tolerance variances of accepted tolerances may bemore or less than a percentage level (e.g., dimension tolerance of lessthan +/−1%). Some relativity between items may range from a differenceof less than a percentage level to a few percent. Other relativitybetween items may range from a difference of a few percent to magnitudeof differences.

As may also be used herein, the term(s) “configured to”, “operablycoupled to”, “coupled to”, and/or “coupling” includes direct couplingbetween items and/or indirect coupling between items via an interveningitem (e.g., an item includes, but is not limited to, a component, anelement, a circuit, and/or a module) where, for an example of indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.

As may even further be used herein, the term “configured to”, “operableto”, “coupled to”, or “operably coupled to” indicates that an itemincludes one or more of power connections, input(s), output(s), etc., toperform, when activated, one or more its corresponding functions and mayfurther include inferred coupling to one or more other items. As maystill further be used herein, the term “associated with”, includesdirect and/or indirect coupling of separate items and/or one item beingembedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may be used herein, one or more claims may include, in a specificform of this generic form, the phrase “at least one of a, b, and c” orof this generic form “at least one of a, b, or c”, with more or lesselements than “a”, “b”, and “c”. In either phrasing, the phrases are tobe interpreted identically. In particular, “at least one of a, b, and c”is equivalent to “at least one of a, b, or c” and shall mean a, b,and/or c. As an example, it means: “a” only, “b” only, “c” only, “a” and“b”, “a” and “c”, “b” and “c”, and/or “a”, “b”, and “c”.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, “processing circuitry”, and/or “processing unit”may be a single processing device or a plurality of processing devices.Such a processing device may be a microprocessor, micro-controller,digital signal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, processing circuitry, and/or processing unitmay be, or further include memory and/or an integrated memory element,which may be a single memory device, a plurality of memory devices,and/or embedded circuitry of another processing module, module,processing circuit, processing circuitry, and/or processing unit. Such amemory device may be a read-only memory, random access memory, volatilememory, non-volatile memory, static memory, dynamic memory, flashmemory, cache memory, and/or any device that stores digital information.Note that if the processing module, module, processing circuit,processing circuitry, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,processing circuitry and/or processing unit implements one or more ofits functions via a state machine, analog circuitry, digital circuitry,and/or logic circuitry, the memory and/or memory element storing thecorresponding operational instructions may be embedded within, orexternal to, the circuitry comprising the state machine, analogcircuitry, digital circuitry, and/or logic circuitry. Still further notethat, the memory element may store, and the processing module, module,processing circuit, processing circuitry and/or processing unitexecutes, hard coded and/or operational instructions corresponding to atleast some of the steps and/or functions illustrated in one or more ofthe Figures. Such a memory device or memory element can be included inan article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with one or more other routines. In addition, a flow diagrammay include an “end” and/or “continue” indication. The “end” and/or“continue” indications reflect that the steps presented can end asdescribed and shown or optionally be incorporated in or otherwise usedin conjunction with one or more other routines. In this context, “start”indicates the beginning of the first step presented and may be precededby other activities not specifically shown. Further, the “continue”indication reflects that the steps presented may be performed multipletimes and/or may be succeeded by other activities not specificallyshown. Further, while a flow diagram indicates a particular ordering ofsteps, other orderings are likewise possible provided that theprinciples of causality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

While transistors may be shown in one or more of the above-describedfigure(s) as field effect transistors (FETs), as one of ordinary skillin the art will appreciate, the transistors may be implemented using anytype of transistor structure including, but not limited to, bipolar,metal oxide semiconductor field effect transistors (MOSFET), N-welltransistors, P-well transistors, enhancement mode, depletion mode, andzero voltage threshold (VT) transistors.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form asolid-state memory, a hard drive memory, cloud memory, thumb drive,server memory, computing device memory, and/or other physical medium forstoring digital information.

As applicable, one or more functions associated with the methods and/orprocesses described herein can be implemented via a processing modulethat operates via the non-human “artificial” intelligence (AI) of amachine. Examples of such AI include machines that operate via anomalydetection techniques, decision trees, association rules, expert systemsand other knowledge-based systems, computer vision models, artificialneural networks, convolutional neural networks, support vector machines(SVMs), Bayesian networks, genetic algorithms, feature learning, sparsedictionary learning, preference learning, deep learning and othermachine learning techniques that are trained using training data viaunsupervised, semi-supervised, supervised and/or reinforcement learning,and/or other AI. The human mind is not equipped to perform such AItechniques, not only due to the complexity of these techniques, but alsodue to the fact that artificial intelligence, by its verydefinition—requires “artificial” intelligence—i.e., machine/non-humanintelligence.

As applicable, one or more functions associated with the methods and/orprocesses described herein can be implemented as a large-scale systemthat is operable to receive, transmit and/or process data on alarge-scale. As used herein, a large-scale refers to a large number ofdata, such as one or more kilobytes, megabytes, gigabytes, terabytes ormore of data that are received, transmitted and/or processed. Suchreceiving, transmitting and/or processing of data cannot practically beperformed by the human mind on a large-scale within a reasonable periodof time, such as within a second, a millisecond, microsecond, areal-time basis or other high speed required by the machines thatgenerate the data, receive the data, convey the data, store the dataand/or use the data.

As applicable, one or more functions associated with the methods and/orprocesses described herein can require data to be manipulated indifferent ways within overlapping time spans. The human mind is notequipped to perform such different data manipulations independently,contemporaneously, in parallel, and/or on a coordinated basis within areasonable period of time, such as within a second, a millisecond,microsecond, a real-time basis or other high speed required by themachines that generate the data, receive the data, convey the data,store the data and/or use the data.

As applicable, one or more functions associated with the methods and/orprocesses described herein can be implemented in a system that isoperable to electronically receive digital data via a wired or wirelesscommunication network and/or to electronically transmit digital data viaa wired or wireless communication network. Such receiving andtransmitting cannot practically be performed by the human mind becausethe human mind is not equipped to electronically transmit or receivedigital data, let alone to transmit and receive digital data via a wiredor wireless communication network.

As applicable, one or more functions associated with the methods and/orprocesses described herein can be implemented in a system that isoperable to electronically store digital data in a memory device. Suchstorage cannot practically be performed by the human mind because thehuman mind is not equipped to electronically store digital data.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A computer comprises: a computing entity (CE)processing core section; a technology level (TL) co-processor section; asystem database section for storing a plurality of TL data operandsregarding a plurality of quantified technologies; a memory section thatstores: a CE operating system; a TL operating system; a plurality of TLsystem applications, where a TL system application of the plurality ofTL system applications includes a machine learning and/or artificialintelligence (ML/AI) system program; and a plurality of TL userapplications, where a TL user application of the plurality of TL userapplications includes an ML/AI user program, wherein, when enabled: thecomputing entity processing core section executes the TL operatingsystem to: control access between the CE operating system and the TLsystem applications; and control access between the CE operating systemand the TL user applications; the CE processing core section executesthe CE operating system to: control access between the TL operatingsystem and the TL co-processor section, and control access between theTL operating system and the system database section; and the TLco-processor section executes one or more of the plurality of TL systemapplications, in accordance with control of the TL operating system andthe CE operating system, to: create TL data operands regarding aquantified technology of the plurality of TL data operands regarding theplurality of quantified technologies from a plurality of ingesteddigital documents; and store the TL data operands in database records ofthe system database section, wherein the plurality of ingested digitaldocuments include a plurality of MSBTP documents (marketing, sales,business, technical, and/or patent), wherein the TL co-processor sectioncreates the TL data operands by: retrieving database records from thesystem database section for the plurality of MSBTP documents;determining technical challenges from data of the database records ofthe MSBTP documents; determining a level of innovation from thetechnical challenges; and determining ideal protection for the level ofinnovations, wherein the technical challenges, the level of innovations,and the ideal protection are TL data operands.
 2. The computer of claim1, wherein the TL co-processor section further executes the one or moreof the plurality of TL system applications by: determining a set ofproblems for a technical challenge of the technical challenges, whereinthe set of problems includes one or more problems; determining a set ofinventive concepts for a problem of the set of problems, wherein the setof inventive concepts includes one or more inventive concepts;determining a set of solutions from an inventive concept of the set ofinventive concepts, wherein the set of solutions includes one or moresolutions; and determining a set of inventive embodiments from asolution of the set of solutions, wherein the set of inventiveembodiments includes one or more inventive embodiments, wherein the setof inventive embodiments is at least a portion of the level ofinnovation.
 3. The computer of claim 1, wherein the TL co-processorsection further executes the one or more of the plurality of TL systemapplications by: retrieving database records from the system databasesection of a set of other quantified technologies of the plurality ofquantified technologies based on a correlation of the quantifiedtechnology with the set of other quantified technologies, wherein theset of other quantified technologies includes one or more otherquantified technologies; interpreting the technical challenges of theset of other quantified technologies to determine a nature of thetechnical challenges of the other quantified technologies; expanding atechnical challenge of the technical challenges for the quantifiedtechnology based on the nature of the technical challenges of the otherquantified technologies.
 4. The computer of claim 1, wherein the TLco-processor section further executes the one or more of the pluralityof TL system applications by: retrieving a technology map from thesystem database section, wherein the technology map provides ahierarchical and/or functional relationship of a group of quantifiedtechnologies of the plurality of quantified technologies; interpretingthe technology map to identify another quantified technology of thegroup of quantified technologies for which a technical challenge of thetechnical challenges is applicable; when the quantified technology isadaptable for use in a market of the other quantified technology,expanding market use of the technical challenge to include the market ofthe other quantified technology; and when the quantified technology isadaptable to accommodate a unique value proposition and/or marketablefeature of the other quantified technology, expanding the technicalchallenges to include a new technical regarding accommodating the uniquevalue proposition and/or the marketable feature of the other quantifiedtechnology.
 5. The computer of claim 1, wherein the TL co-processorsection further executes the one or more of the plurality of TL systemapplications by: retrieving a technology map from the system databasesection, wherein the technology map provides a hierarchical and/orfunctional relationship of a group of quantified technologies of theplurality of quantified technologies; and determining a level ofdisruption that the quantified technology will have on the group ofquantified technologies based on the technical challenges of thequantified technology, wherein the level of disruption is a factor indetermining the level of innovation.
 6. The computer of claim 1, whereinthe TL co-processor section further executes the one or more of theplurality of TL system applications by: determining generational datafrom the data of the database records of the MSBTP documents, whereinthe generational data includes a start of a generation of the quantifiedtechnology, a life span for the quantified technology, and phases of thegeneration; and determining a level of fundamental innovation, a levelof commercially necessary innovation, and a level of commercialexpansion innovation based on the generational data and the level ofinnovation.
 7. The computer of claim 1, wherein the TL co-processorsection further executes the one or more of the plurality of TL systemapplications by: determining a total number of inventions based on thelevel of innovation; and determining an ideal number of inventions ofthe total number of inventions to protect to establish the idealprotection.
 8. The computer of claim 1 further comprises: the technologylevel co-processor section executes the TL user application, inaccordance with control of the TL operating system and the CE operatingsystem, to: determine a number of inventions regarding the quantifiedtechnology to protect based on the ideal protection and a patentposition; generate a period by period digital representation of thenumber of inventions based on life span of the quantified technology andphases of the life span; and store, in the system database section, thedigital representation of the period by period digital representation ofthe number of inventions in a system database record associated with thequantified technology.
 9. The computer of claim 8, wherein thetechnology level co-processor section further executes the TL userapplication to: determine period-by-period values of the quantifiedtechnology based on the number of inventions, the ideal protection, thepatent position, and period-by-period market impact data of thequantified technology retrieved from the system database section;determine period-by-period encumbrances of the number of inventions toprotect; generate an architectural design regarding protectinginventions of the quantified technology based on the period-by-periodvalues of the quantified technology, the period-by-period encumbrances,the patent position, and the number of inventions to protect; generate agraphical representation of the architectural design for display; andstore the graphical representation of the architectural design in aprivate database of the computer.
 10. The computer of claim 1 furthercomprises: the computing entity (CE) processing core section includingone or more processing cores; the technology level (TL) co-processorsection including one or more co-processors; and the system databasesection including one or more databases.